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time series analysis

606 papers and 33 presentations; 594 titles.

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Conference × Year × Title × Authors Extras Pages
PharmaSUG 2026 Be a Multi-Media Wizard: Make Your Output Dance and Sing LeRoy Bessler source 49
PharmaSUG 2026 Implementing Dynamic Time Warping in SAS 9.4 Using PROC IML: An Alternative Approach for Time-Series Model Evaluation Yida Bao,
Philippe Gaillard,
Wei Yao,
Zheng Zhang,
Rui Wang		 source 13
PharmaSUG 2026 The Best Data Dashboard Alternative: More Efficient But Equally Effective Performance Monitoring and Reporting LeRoy Bessler source 8
PHUSE EU 2025 Collaborative Industry Open-Source Solutions for Clinical Trial Quality Management Björn Koneswarakantha,
Frederik Collin		 source
presentation source		 9
MWSUG 2025 Large-Scale Time Series Forecasting in Model Studio Danny R. Modlin source 39
SESUG 2025 Large-Scale Time Series Forecasting in Model Studio Danny R. Modlin 39
SESUG 2025 Modeling and Forecasting Wildfire Trends in Colorado, Montana, Utah, and Wyoming: A Spatio-Temporal Approach with R Princess Tagoe 14
SESUG 2025 Time Series Analysis and Forecasting of U.S. Teenage Female Unemployment Sekyiwaah Nuamah 21
SESUG 2025 Time Series Analysis of Quarterly Air Traffic Passenger Counts at San Francisco International Airport Trenzy Odero,
Mostafa Zahed		 16
WUSS 2025 Large-Scale Time Series Forecasting in Model Studio Danny R. Modlin source 39
MWSUG 2024 Bessler's Principles of Communication-Effective Data Visualization [presentation] LeRoy Bessler source 125
SESUG 2024 Forecasting U.S. Unemployment Rates Using ARIMA: A Time Series Analysis from 1948 to 2019 Shanice Douglas source 11
SESUG 2024 Leveraging SAS/IML for Audio Source Separation Katharine Mary Scott source 13
SESUG 2024 Who's Bringing That Big Data Energy? A 47-Year Longitudinal Analysis of 30,000 Presentations in the SAS User Community To Elucidate Top Contributors and Rising Stars Troy Martin Hughes source 36
PharmaSUG 2024 Leadership Lessons from Another Life: How my Previous Career Helped Me as a Statistician Christiana Hawn,
Lily Ray		 source 5
PHUSE US 2024 Collaborative Development of a Clinical Trial Data Anomaly Detection Tool within an Industry Consortium Pekka Tiikkainen source
presentation source		 6
WUSS 2023 A Beginner's Step-by-Step Guide to Digital Marketing Data Mining and Analysis Using SAS Mahsa Tahmasebi Ghorabi,
Leon Rod Davoody		 source 7
WUSS 2023 Who's Bringing That Big Data Energy? A 47-Year Longitudinal Analysis of 30,000 Presentations in the SAS User Community To Elucidate Top Contributors and Rising Stars Troy Martin Hughes source 36
SESUG 2023 Forecasting Goals for Student Success Metrics in Accountability Performance Reporting using SAS Visual Analytics Xiaoying Liu,
Hennadii Balashov		 source 9
SESUG 2023 Getting to Know the SAS Data Access Engine: SASEFRED Paul Newsom source 14
SESUG 2023 Pol-y-mor-phism in SAS, Or, Good Programmers are Lazy David B. Horvath source 21
SESUG 2023 Unobserved Components Models: Applications in Post-COVID Analysis David J. Corliss source 10
PHUSE EU 2022 Finding Anomalies and Outliers in Clinical Trial Time Series Data Pekka Tiikkainen source
presentation source		 6
SESUG 2022 Pol-y-mor-phism in SAS, Or, Good Programmers are Lazy David B. Horvath source 21
SESUG 2022 Statistical Analysis of School Shootings in the United States as Stochastic Terrorism David J. Corliss source 8
PharmaSUG 2022 Potential features analysis affect Covid-19 spread Yida Bao,
Philippe Gaillard		 source 11
PHUSE US 2022 Using the Geometric Properties of Datasets to Analyze the Accuracy of COVID-19 Forecasting Models [presentation] Irina Kotenko,
Kostiantyn Drach		 source 30
SGF 2021 Disproportional Impact of COVID-19 on Marginalized Communities David J. Corliss source
presentation		 10
SGF 2021 Large-scale demand forecasting for e-commerce retailer using SAS Forecast Studio: A Case Study Ajay Kumar Mishra,
Mohak Narkhede,
Padmanabha Chandu Saladi		 source 9
SGF 2021 Prediction of Parkinson's Disease With a Regression Model Using Vertical Ground Reaction Force Data Jin Ge,
Tianchen Xu,
Jia Guo,
Mengyu Zhang		 source
presentation		 7
SGF 2021 SAS Time Series Analysis & Forecasting (TSAF) at the Canada Revenue Agency (CRA), with COVID impacts Jason A. Oliver source
presentation		 22
PHUSE EU 2020 Catch Them When You Can ... Fix Them [presentation] Anna Panasenko source
video		 23
PHUSE EU 2020 Understanding the Spread of COVID-19 in the United States Using Topology and Machine Learning for Time Series Iryna Kotenko,
Kostiantyn Drach		 source
video
presentation source		 32
SGF 2020 An Introduction to Multiple Time Series Analysis and the VARMAX Procedure Xilong Chen source 19
SGF 2020 Building Two Regression Lines Is Better Than Building One [presentation] G Liu source 8
SGF 2020 Forecasting Healthcare Statistics At the Cleveland Clinic Michael Bromley source 10
SGF 2020 History Carried Forward, Future Carried Back: Mixing Time Series of Differing Frequencies Mark Keintz source 14
SGF 2020 Is it possible to reduce smoking by increasing taxes? An analysis on Danish data using SAS software Anders Milhøj source 13
SGF 2020 Neural-Network Based Forecasting Strategies in SAS Viya Steven C. Mills source 14
SGF 2020 Reducing Ecological Footprint: Examining Panel Data Neil Belford source 7
SGF 2020 Scalable Cloud-Based Time Series Analysis and Forecasting Using Open Source Software Javier Delgado source 21
SGF 2020 Show Me the Money! Preparing Economics Students for Data Science Careers Steven C. Myers source 19
SGF 2020 Simulating Time Series Analysis Using SAS - Part II Cointegration [presentation] Ismail E. Mohamed source 24
SGF 2020 Solving the VAST Challenge: Three Case Studies Using SAS Visual Analytics Riley Benson source 17
SGF 2020 Time After Time: D-I-D and ITS Models in SAS Margaret Warton source 21
SGF 2020 Visual Data Insights: Image and Ranked Precise Values for Quick, Easy, and Reliable Inference LeRoy Bessler source 20
SGF 2020 Visualizing Geographical Data with a Tile Grid Map in SAS Lingxiao Li source 13
PharmaSUG 2020 Pattern Detection for Monitoring Adverse Events in Clinical Trials - Using Real Time, Real World Data Surabhi Dutta source 20
SESUG 2019 Intervention at the Library: Assessing the Effect of an Event David A. Dickey,
John Vickery		 source 19
SESUG 2019 The Best of Both Worlds: Forecasting Using Time Series with Inputs David A. Dickey source 19
SESUG 2019 Time Series Forecasting using PROC MCMC SESUG 2019 Murali Sastry,
Tyler Hicks		 source 16
MWSUG 2019 Exploring and characterizing time series data in a non-regression based approach Steven C. Myers 20
MWSUG 2019 Taxi Ride Prediction: Does the Yellow Cab Supply Meet Customer Demands? Sreejita Biswas,
Miriam McGaugh		 12
MWSUG 2019 The Advent of Renewable Energy Sai Teja Sagi,
Miriam McGaugh		 21
PharmaSUG 2019 History Carried Forward, Future Carried Back: Mixing Time Series of Differing Frequencies Mark Keintz source 11
PharmaSUG 2019 Merging Sensor Data with Patient Records in Clinical Trials - Systems and Benefits Surabhi Dutta,
Shubhranshu Dutta		 source 9
PharmaSUG 2019 The Power of PROC FORMAT Jonas V. Bilenas,
Kajal Tahiliani		 source 13
SGF 2019 A Selective Overview of Panel Data with Applications in SAS Oral Capps source 26
SGF 2019 Fit Statistic Smoothing: Minimizing Bias in Time Series Forecasting Zachary D. Blizard source 12
SGF 2019 Follow My Lead: Designing Accessible Reports by Example Using SAS Visual Analytics Jesse Sookne source 18
SGF 2019 How to Use Deep Learning with Your Internet of Things (IoT) Digital Twin Bradley W. Klenz source 9
SGF 2019 Identifying Seasonality and Trend with a Cycle Plot in SAS Lingxiao Li source 10
SGF 2019 IFRS9: Using SAS/ETD Software and SAS Studio to Select Macro Economic Variables Julio Alberto Campa Vega Filho source 19
SGF 2019 Ten Underused Features That Improve Your SAS Forecast Server Workflow Evan Anderson,
Michael J. Leonard		 source 18
SGF 2019 Text Analytics at British Airways Simon Cumming source 18
SGF 2019 The Bayesians are Coming! The Bayesians are Coming! The Bayesians Are Coming to Time Series! Aric LaBarr source 13
SGF 2019 The Best of Both Worlds: Forecasting Using Time Series with Inputs David A. Dickey source 19
SGF 2019 Using ETS Software for Intervention Models for Sales of Cars Anders Milhøj source 8
SGF 2019 Using SAS Forecast Server and the SASEFRED Engine to Enhance Your Forecast Catherine LaChapelle source 7
SGF 2019 Writing a Gradient Boosting Model Node for SAS Visual Forecasting Yue Li,
Jingrui Xie,
Iman Vasheghani Farahani		 source 19
PHUSE US 2019 Optimizing Over Time Plots Via Analytics Kishore Pothuri,
Mayank Choudhary		 source
poster source		 5
SESUG 2018 A Case Study of Mining Social Media Data for Disaster Relief: Hurricane Irma Hurricane Irma source 11
SESUG 2018 Forecasting: Something Old, Something New David A. Dickey source 26
SESUG 2018 Predictive Modeling for Healthcare Professionals: The use of time-series analysis for health-related data and the application of ARIMA modeling techniques in SAS for Public Health Practice Camillia R. Comeaux source 6
SESUG 2018 Understanding Crime Pattern in United States by Time Series Analysis using SAS Tools Soumya Ranjan Kar Choudhury source 6
WUSS 2018 Forecasting: Something Old, Something New David A. Dickey source 26
WUSS 2018 Time Series Analysis of Hate Speech in Social Media David J. Corliss source 8
PharmaSUG 2018 SAS Macros of Performing Look-Ahead and Look-Back Reads Yanhong Liu source 10
PharmaSUG 2018 Using SAS GTL to Visualize Data When there is Too Much of It to Visualize Nathaniel Derby,
Perry Watts		 source 22
SGF 2018 A Case Study of Mining Social Media Data for Disaster Relief: Hurricane Irma Bogdan Gadidov,
Linh H. Le		 source 11
SGF 2018 Analytics Applications in Targeted Marketing and Forecasting Demand: A Two-Stage Model Anurag Hardikar source 7
SGF 2018 Bitcoin Price Forecasting Using Web Search and Social Media Data Travis Miller source 22
SGF 2018 Building Revenue Management Decision Support Platforms with SAS Eric Schmidt source 6
SGF 2018 Distribution Circuit Load Forecasting Using Advanced Metering Infrastructure Data Prasenjit Shil,
Tom Anderson		 source 12
SGF 2018 Forecasting: Something Old, Something New David A. Dickey source 26
SGF 2018 Getting More Insight into Your Forecast Errors with the GLMSELECT and QUANTSELECT Procedures Gerhard Svolba source 26
SGF 2018 Getting Started with Time Series Models [presentation] Danny R. Modlin source 15
SGF 2018 How Good is That Forecast? The Nuances of Prediction Evaluation Across Time Aric LaBarr source 7
SGF 2018 How SAS Helps to Price Auto Insurance in Brazil Anna Mattos source 7
SGF 2018 How to Use Streaming Analytics to Create a Real-Time Digital Twin Bradley W. Klenz source 14
SGF 2018 Mile-High Visual Analytics: Ways to Enhance Reports and Dashboards Scott P. Leslie source 13
SGF 2018 Regime-Switching Models: Capturing Structural Changes in Time Series Xilong Chen,
Ji Shen		 source 14
SGF 2018 SAS Visual Forecasting: A Cloud-Based Time Series Analysis and Forecasting System Jerzy M. Brzezicki,
Joseph H. Katz		 source 21
SGF 2018 Scalable Cloud-Based Time Series Analysis and Forecasting Thiago Quirino,
Michael J. Leonard,
Ed Blair		 source 22
SGF 2018 Shorter Waiting Time, Better Emergency Healthcare: Forecasting Stockholms' Emergency Room Visits Martin Nordberg,
Oskar Eriksson		 source 24
SGF 2018 Time Series Analysis of Hate Speech in Social Media David J. Corliss source 12
SGF 2018 Time Series Feature Extraction Michele A. Trovero,
Michael J. Leonard		 source 18
SGF 2018 Top 10 Tips for SAS Enterprise Miner Based on 20 Years' Experience Melodie Rush source 21
SESUG 2017 Leads and Lags: Static and Dynamic Queues in the SAS DATA STEP, 2nd ed. Mark Keintz source 15
MWSUG 2017 An Array of Possibilities: Manipulating Longitudinal Survey Data with Arrays Lakhpreet Gill 8
MWSUG 2017 Demystifying Intervals Derek P. Morgan 15
MWSUG 2017 If You Build It, Will They Understand? Designing Reports for the General Public in SAS Visual Analytics Jesse Sookne,
Ed Summers,
Julianna Langston,
Karen Mobley		 20
MWSUG 2017 Lag Models with Social Response Outcomes David J. Corliss 9
WUSS 2017 Standardized Approaches for Analyzing Quality Improvement Interventions in Healthcare Settings Polina Kukhareva source 20
SGF 2017 Analyzing the Effect of Weather on Uber Ridership Anusha Mamillapalli,
Singdha Gutha		 source
pdf		 10
SGF 2017 Automatic Singular Spectrum Analysis and Forecasting Michael J. Leonard,
Bruce Elsheimer		 source 18
SGF 2017 Creating Daily Rolling 6-Month Average and Cumulative Enrollment Graphs Using PROC EXPAND and INTNX Susan Schleede source 10
SGF 2017 Detecting and Adjusting Structural Breaks in Time Series and Panel Data Using the SSM Procedure Rajesh S. Selukar source 18
SGF 2017 Find Daylight Saving Time and Forget It Chao-Ying Hsieh source 4
SGF 2017 Hash Objects: When LAGging Behind Just Doesn't Work Andrea Wainwright-Zimmerman source 5
SGF 2017 Identifying Abnormal Equipment Behavior and Filtering Data near the Edge for IoT Applications Ryan Gillespie,
Saurabh Gupta		 source 5
SGF 2017 Interrupted Time Series Power Calculation using DO Loop Simulations Nigel Rozario,
Andrew McWilliams,
Charity Moore		 source 15
SGF 2017 Leads and Lags: Static and Dynamic Queues in the SAS DATA STEP, 2nd ed. Mark Keintz source 15
SGF 2017 Multivariate Time Series: Recent Additions to the VARMAX Procedure Xilong Chen,
Stefanos Kechagias		 source
zip		 14
SGF 2017 Nine Best Practices for Big Data Dashboards Using SAS Visual Analytics Elena Snavely source 7
SGF 2017 Outline Outliers: Adding a Business Sense Alex Glushkovsky source 17
SGF 2017 Production Forecasting in the Age of Big Data in the Oil and Gas Industry [presentation] Vipin Prakash Gupta,
Satyajit Dwivedi		 source 17
SGF 2017 Temporal Text Mining: A Thematic Exploration of Don Quixote Ray Wright source 16
SGF 2017 Time Series Analysis and Forecasting in SAS University Edition Christopher Battiston source 10
SGF 2017 Time-Frequency Analysis Using SAS Michael J. Leonard,
Wei Xiao,
Arin Chaudhuri		 source 5
SGF 2017 Timing is Everything: Detecting Important Behavior Triggers Daymond Ling source 12
SGF 2017 Using SAS Viya Microservices Logging for Performance Analysis of SAS Visual Analytics 8.1 Reports Scott C. Sweetland source 9
SGF 2017 Using Vibration Spectral Analysis to Predict Failures by Integrating R into SAS Asset Performance Analytics Adriaan Van Horenbeek source 15
SCSUG 2016 Effective method on curing heart disease K. Varadarajan,
Surya Bhaskar Ayyalasomayajula		 source 12
SESUG 2016 Dynamically Changing Time Zones and Daylight Savings on Time Series Data Chao-Ying Hsieh source 6
SESUG 2016 Factors of Multiple Fatalities in Car Crashes Bill Bentley,
Gina Colaianni,
Kennedy Onzere,
Cheryl Joneckis,
Xuelei (Sherry) Ni		 source 62
SESUG 2016 Identifying Gaps in Time Series Data Identifying Gaps source 8
SESUG 2016 Leads and Lags: Static and Dynamic Queues in the SAS DATA STEP Mark Keintz source 15
SESUG 2016 Tales from the Help Desk 7: Solutions to Common SAS Tasks Bruce F. Gilsen source 11
MWSUG 2016 Analyzing the Effect of Weather on Uber Ridership Snigdha Gutha,
Anusha Mamillapalli		 11
MWSUG 2016 Establishing Similarity of Modeled and Experimental PK/PD Hysteretic Loops using Pseudo Time Series Analysis and Dynamic Time Warping Ron Smith 18
MWSUG 2016 Leads and Lags: Static and Dynamic Queues in the SAS DATA STEP Mark Keintz 15
WUSS 2016 Did the Protocol Change Work? Interrupted Time Series Evaluation for Health Care Organizations. Carol Conell,
Alexander C. Flint		 source 14
SGF 2016 A Multistage Modeling Strategy for Hierarchical Demand Forecasting Pu Wang source 11
SGF 2016 Breakthroughs at Old Dominion Electric Cooperative with Energy Load Forecasting Innovation David Hamilton,
Steve Becker,
Emily Forney		 source 19
SGF 2016 Case Study Using SAS Forecast Studio: Daily Taxi Data from New York City [presentation] Simon Sheather source 47
SGF 2016 Case Study: SAS Visual Analytics Dashboard for Pollution Analysis Viraj R Kumbhakarna source 12
SGF 2016 Credit Card Interest and Transactional Income Prediction with an Account-Level Transition Panel Data Model Using SAS/STAT and SAS/ETS Software Denys Osipenko source 20
SGF 2016 Dynamic Forecast Aggregation Michael J. Leonard source 9
SGF 2016 Factors of Multiple Fatalities in Car Crashes Bill Bentley,
Gina Colaianni,
Cheryl Joneckis,
Sherry Ni,
Kennedy Onzere		 source 60
SGF 2016 Forecasting Short Time Series Using SAS Forecast Server Cobey Abramowski,
Christian Haxholdt,
Chris Houck,
Benjamin Perryman		 source 5
SGF 2016 From Sensors to Solutions: An Example of Analytics in Motion Milad Falahi,
Gilbert Hernandez		 source 12
SGF 2016 If You Build It, Will They Understand? Designing Reports for the General Public in SAS Visual Analytics Jesse Sookne,
Julianna Langston,
Karen Mobley,
Ed Summers		 source 20
SGF 2016 Leads and Lags: Static and Dynamic Queues in the SAS DATA STEP Mark Keintz source 15
SGF 2016 Rapid Prototyping: Accelerating Development of Your Organization's Reports Using SAS Visual Analytics Elliot Inman,
Michael Drutar		 source 19
SGF 2016 Real-Time Predictive Modeling of Key Quality Characteristics Using Regularized Regression: SAS Procedures GLMSELECT and LASSO Jon M. Lindenauer source 10
SGF 2016 Similarity Analysis: an Introduction, a Process, and a Supernova David J. Corliss source 11
SGF 2016 Simultaneous Forecasts of Multiple Interrelated Time Series with Markov Chain Model Gongwei Chen source 11
SGF 2016 Time Series Analysis: U.S. Military Casualties in the Pacific Theater during World War II Rachael Becker source
presentation		 20
SGF 2016 Using Predictive Analysis to Optimize Pharmaceutical Marketing Xue Yao source 6
SGF 2016 What's the Difference? David A. Dickey source 17
SCSUG 2015 Using SAS Software to Determine the Mixed Rotterdam Demand Model Parameters and Test Statistical References Maryam Tabarestani,
Hector Zapata		 23
SESUG 2015 Analysis of the Impact of Federal Funds Rate Change on US Treasuries Returns using SAS Svetlana Gavrilova source 31
SESUG 2015 Becker 133 SESUG 2015 1 Time Series Analysis U.S. Military Casualties,
Rachael Becker		 source 17
WUSS 2015 Exploring SAS Visual Analytics capabilities to go from Fat to Fit! Viraj R Kumbhakarna source 22
WUSS 2015 How much is $1 worth? Ross Lallian source 13
WUSS 2015 Leads and Lags: Static and Dynamic Queues in the SAS DATA STEP Mark Keintz source 15
SGF 2015 "Out Here" Forecasting: A Retail Case Study Chris Houck source 9
SGF 2015 An Introduction to Testing for Unit Roots Using SAS: The Case of U.S. National Health Expenditures Don McCarthy source
zip		 6
SGF 2015 An Overview of Econometrics Tools in SAS/ETS: Explaining the Past and Modeling the Future: Mark Little,
Kenneth Sanford		 source 13
SGF 2015 Analyzing Parking Meter Transactions Using SAS Procedures Anders Milhøj source 12
SGF 2015 Count Series Forecasting Michael J. Leonard source 14
SGF 2015 Demystifying Date and Time Intervals Derek P. Morgan source 13
SGF 2015 Forecasting Vehicle Sharing Demand Using SAS Forecast Studio Kushal Kathed,
Goutam Chakraborty,
Ayush Priyadarshi		 source 9
SGF 2015 How to Hunt for Utility Customer Electric Usage Patterns Armed with SAS Visual Statistics with Hadoop and Hive Kathy Ball source 12
SGF 2015 Incorporating External Economic Scenarios into Your CCAR Stress Testing Routines Kenneth Sanford,
Christian Macaro		 source 10
SGF 2015 Leads and Lags: Static and Dynamic Queues in the SAS DATA STEP Mark Keintz source
zip		 14
SGF 2015 Member-Level Regression Using SAS Enterprise Guide and SAS Forecast Studio Leigh McCormack,
Prudhvidhar Perati		 source 8
SGF 2015 Meter Data Analytics--Enabling Actionable Decisions to Derive Business Value from Smart Meter Data Tom Anderson,
Jennifer Whaley		 source 11
SGF 2015 SAS Analytics plus Warren Buffett's Wisdom Beats Berkshire Hathaway! Huh? Bruce Bedford source 20
SGF 2015 Strengthening Diverse Retail Business Processes with Forecasting: Practical Application of Forecasting Across the Retail Enterprise Alex Chien,
Elizabeth Cubbage,
Wanda Shive		 source 21
SGF 2015 The bookBot Ultimatum! David A. Dickey,
John Vickery		 source
zip		 19
SGF 2015 Time Series Modeling and Forecasting--An Application to Stress-Test Banks Ania Supady source 13
SGF 2015 Twelve Ways to Better Graphs LeRoy Bessler source 20
SGF 2015 Using SAS to Combine Regression and Time Series Analysis on U.S. Financial Data to Predict the Economic Downturn Avinash Kalwani,
Nishant Vyas		 source 6
SGF 2015 Want an Early Picture of the Data Quality Status of Your Analysis Data? SAS Visual Analytics Shows You How Gerhard Svolba source
zip		 19
SGF 2015 Your Database Can Do SAS Too! Harry Droogendyk source 18
SESUG 2014 Time Series Mapping with SAS: Visualizing Geographic Change over Time in the Health Insurance Industry Barbara B. Okerson source 8
MWSUG 2014 Use of Social Media Data to Predict Retail Sales Performance Li Zhang 13
MWSUG 2014 Visualization of Self-Reported Alcohol Use Data: A Timeline Followback Dashboard using Heatmaps, Time Series Plots, and HTML Hover-Text Daniel Fuhrmann,
Michael Fendrich,
Lisa Berger		 11
WUSS 2014 Analyzing Phased Interventions with Segmented Regression and Stepped Wedge Designs Eric C. Wong,
Po-Han Chen,
Dorothy Hung		 source 9
WUSS 2014 Getting Your Hands on Reproducible Graphics Rebecca Ottesen,
Leanne Goldstein		 source 17
WUSS 2014 Intervals, Enhanced Derek P. Morgan source 12
WUSS 2014 LEADS AND LAGS: HANDLING QUEUES IN THE SAS DATA STEP Mark Keintz source 12
WUSS 2014 Markov Chain Model Forecast for Interrelated Time Series Data Using SAS/IML Gongwei Chen source 10
SGF 2014 CMS Core Measures, the Affordable Care Act, and SAS Visual Analytics Joe Whitehurst,
Diane Hatcher		 source 16
SGF 2014 Communication-Effective Data Visualization: Design Principles, Widely Usable Graphic Examples, and Code for Visual Data Insights LeRoy Bessler source 38
SGF 2014 Create Custom Graphs in SAS Visual Analytics Using SAS Visual Analytics Graph Builder Ravi Devarajan,
Himesh Patel,
Patricia L. Berryman,
Lisa Everdyke		 source 24
SGF 2014 Detecting Patterns Using Geo-Temporal Analysis Techniques in Big Data [presentation] Richard W. La Valley,
Abraham Usher,
Donald J. Henderson,
Paul M. Dorfman		 source 1
SGF 2014 Develop Highly Interactive Web Charts with SAS Rajesh Inbasekaran,
Naren Mudivarthy,
Neetha Sindhu		 source 6
SGF 2014 Disease Prevention to Reduce New Hampshire Health-Care Claims and Costs: A Data Mining Approach [presentation] Rakesh Karn,
Rom Khattri,
Pradeep Podila,
Linda Schumacher		 source 6
SGF 2014 Ex-Ante Forecast Model Performance with Rolling Simulations Michael J. Leonard,
Ashwini Dixit,
Udo Sglavo		 source 18
SGF 2014 Handling Missing Data Using SAS Enterprise Guide Elena Shtern,
Matt Hall		 source 21
SGF 2014 High-Performance Forecasting Using SAS Grid Manager Michael J. Leonard,
Cheryl Doninger,
Udo Sglavo		 source 6
SGF 2014 How Predictive Analytics Turns Mad Bulls into Predictable Animals Marcel Baumgartner source 5
SGF 2014 How to Separate Regular Prices from Promotional Prices? Michael J. Leonard,
Michele A. Trovero		 source 7
SGF 2014 Intermittent Demand Forecasting and Multi-tiered Causal Analysis Edward Katz source 11
SGF 2014 Multivariate Time Series Modeling Using PROC VARMAX Anders Milhøj source 16
SGF 2014 Predictive Analytics Reporting Framework [presentation] Heidi Hiemstra source 6
SGF 2014 Speed Dating: Looping Through a Table Using Dates Scott Fawver source 5
SGF 2014 Text Mining Economic Topic Sentiment for Time Series Modeling Michael P. Dessauer,
Justin Kauhl		 source 14
SGF 2014 The Desert and the Dunes: Finding Oases and Avoiding Mirages with the SAS Visual Analytics Explorer Nascif Abousalh-Neto source 15
SGF 2014 Time Contour Plots David J. Corliss source 9
SGF 2014 Time Series Mapping with SAS: Visualizing Geographic Change over Time in the Health Insurance Industry Barbara B. Okerson source 8
SGF 2014 Using SAS Graph Template Language with SAS 9.3 Updates to Visualize Data When There is Too Much Data to Visualize Perry Watts,
Nathaniel Derby		 source 20
SGF 2014 What's New in SAS Enterprise Miner 13.1 Jared Dean,
Jonathan Wexler		 source 16
SGF 2014 When Do You Schedule Preventative Maintenance? Multivariate Time Series in SAS/ETS Kenneth Sanford source 8
WUSS 2013 An Algorithm for ARIMA Dynamic Regression Variable Selection Ross Bettinger source 14
WUSS 2013 Dynamic Regression in ARIMA Modeling Ross Bettinger source 11
WUSS 2013 Using PROC ARIMA to Model Trends in US Home Prices Ross Bettinger source 13
SESUG 2013 Forecasting Enrollment in Higher Education using SAS Forecast Studio Forecasting Enrollment source 5
MWSUG 2013 Leading and Lagging Indicators in SAS David J. Corliss 8
MWSUG 2013 Time Contour Plots David J. Corliss 11
MWSUG 2013 Use SAS/ETS to Forecast Credit Loss for CCAR Xinpeng (Tom) Wang 4
NESUG 2013 Arrays Plus Data Step Plus Cramer's Rule = Fast Rolling Regresions Mark Keintz 15
NESUG 2013 Leads and Lags in SAS Mark Keintz 11
NESUG 2013 Time Contour Plots David J. Corliss 11
PharmaSUG 2013 Data Visualization Tips and Techniques for Effective Communication LeRoy Bessler source 55
SGF 2013 Evaluating System-Wide Process Improvement in a Health-Care System: Data Through Analysis Dorothy Hung,
Eric C. Wong,
Lubna Qureshi,
Pragati Kenkare		 source 6
SGF 2013 Exploring Time Series Data Properties in SAS Aude Pujula,
David Maradiaga,
Hector Zapata		 source 12
SGF 2013 Fast Dashboards Anywhere with SAS Visual Analytics Rick Styll source 27
SGF 2013 Integrated Framework for Stress Testing in SAS Jimmy Skoglund,
Wei Chen		 source 11
SGF 2013 Nontemporal ARIMA Models in Statistical Research David J. Corliss source 10
SGF 2013 The Box-Jenkins Methodology for Time Series Models Theresa H. Ngo source 11
SGF 2013 Using Data Mining in Forecasting Problems Chip Wells,
Justin Kauhl,
Timothy Rey		 source 17
NESUG 2012 Introduction to Statistics with Wavelets in SAS David J. Corliss 11
NESUG 2012 Leading and Lagging Indicators in SAS David J. Corliss 8
NESUG 2012 Off the Beaten Path: Create Unusual Graphs with ODS Graphics Prashant Hebbar 26
NESUG 2012 Rolling Regressions with PROC FCMP and PROC REG Mark Keintz 13
NESUG 2012 Using PROC FCMP to Solve Rolling Regression Rapidly Chao Huang,
Liang Xie		 4
NESUG 2012 Using SAS GTL with 9.3 Updates to Visualize Data When There is Too Much of it to Visualize Perry Watts,
Nathaniel Derby		 20
SESUG 2012 SPC Data Visualization of Seasonal and Financial Data Using JMP Diane K. Michelson source 9
MWSUG 2012 Are Sales Figures in Line With Expectations? Using PROC ARIMA in SAS to Forecast Company Revenue Saveth Ho,
Brian Van Dorn		 10
MWSUG 2012 Combined Forecasts: What to Do When One Model Isn't Good Enough Ed Blair,
Michael J. Leonard,
Bruce Elsheimer		 14
MWSUG 2012 Get the Best Out Of SAS ODS Graphics and the SG (Statistical Graphics) Procedures: Communication-Effective Charts, Things That SAS/GRAPH Cannot Do As Well, and Macro Tools To Save Time and Avoid Errors LeRoy Bessler 70
WUSS 2012 Automobile Sales Modeling using Granger-Causality Graph with PROC VARMAX in SAS 9.3 Akkarapol Sa-ngasoongsong source 10
SGF 2012 Analyzing the Time Series of U.S. E-Commerce Using PROC UCM Anders Milhøj source 11
SGF 2012 Application of Time Series Clustering Using SAS Enterprise Miner for a Retail Chain Karthik Nakkeeran,
Satish Garla,
Goutam Chakraborty		 source 9
SGF 2012 Combined Forecasts: What to Do When One Model Isn't Good Enough Ed Blair,
Michael J. Leonard,
Bruce Elsheimer		 source 14
SGF 2012 Comparison of SAS Graphic Alternatives, Old and New LeRoy Bessler source 22
SGF 2012 Creating the Perfect Plot with PROCs EXPAND and SGPLOT: The Dynamic Duo of Time Series Display Andrew H. Karp source 2
SGF 2012 Dynamically Evolving Systems: Cluster Analysis Using Time David J. Corliss source 9
SGF 2012 Let Oil and Gas Talk to You: Predicting Production Performance Keith R. Holdaway source 12
SGF 2012 Off the Beaten Path: Create Unusual Graphs with GTL Prashant Hebbar source
zip		 26
SGF 2012 Predicting Electoral Outcomes with SAS Sentiment Analysis and SAS Forecast Studio Jenn Sykes source 9
SGF 2012 Sparklines in the DATA Step Graphics Interface from SAS/GRAPH Murphy Choy source 7
SGF 2012 Up Close and Personal with SAS Enterprise Guide 5.1 Anand V. Chitale,
Lina Clover		 source 11
SGF 2012 Using SAS GTL to Visualize Your Data when there is Too Much of it to Visualize Perry Watts,
Nathaniel Derby		 source 21
SGF 2012 Variable Selection for Multivariate Cointegrated Time Series Prediction with PROC VARCLUS in SAS Enterprise Miner 7.1 Akkarapol Sa-ngasoongsong,
Satish T. Bukkapatnam		 source 12
SGF 2012 Weighted Portmanteau Tests Revisited: Detecting Heteroscedasticity, Fitting Nonlinear and Multivariate Time Series Thomas J. Fisher source 12
SCSUG 2011 Evaluation of Promotional Campaigns in the Utilities Industry Using a Transfer Function Time-Series Model Fujiang Wen source 10
SESUG 2011 Categorizing the Degradation State of Aircraft Generators using Rank Order Statistics and SAS CLUSTER Procedure Tsung-Hsun Tsai source 6
SESUG 2011 Graphing a Progression of Time Series Plots Nathaniel Derby source 11
SESUG 2011 Time Series Analysis: Separating Overlapping Events M. Scott Elliott source 10
SESUG 2011 Using SAS GTL to Visualize Your Data when there is Too Much of it to Visualize Perry Watts,
>>>>		 source 22
SESUG 2011 Using SAS GTL to Visualize Your Data when there is Too Much of it to Visualize Perry Watts,
>>>>		 source 22
WUSS 2011 Assessing resource adequacy uncertainty in California electricity summer demand using the MCMC procedure in SAS Enterprise MinerTM Miguel Garcia-Cerrutti source 12
WUSS 2011 Graphing a Progression of Time Series Plots with ODS Graphics Nathaniel Derby source 11
WUSS 2011 Using SAS GTL to Visualize Your Data when there is Too Much of it to Visualize Nathaniel Derby source 22
MWSUG 2011 Contour Plots for Time Series Analysis David J. Corliss 11
MWSUG 2011 Does Lawrence Smoking Ban Impact Kansas Liquor Sales? Lijia Mo 12
MWSUG 2011 Dynamically Evolving Systems: Cluster Analysis Using Time David J. Corliss 12
MWSUG 2011 Graphing a Progression of Time Series Plots with ODS Graphics Nathaniel Derby,
Laura Vo,
Perry Watts		 11
MWSUG 2011 JMP as an Analytic Hub: Using JMP to Build Custom Applications via SASand R Kelci J. Miclaus,
Clay Barker,
Jun Ge		 13
MWSUG 2011 Money Demand Estimation using SAS Gerard G Tano 16
MWSUG 2011 Using SAS GTL to Visualize Your Data when there is Too Much of it to Visualize Perry Watts,
Nathaniel Derby		 22
MWSUG 2011 Using SAS to Create Sales Expectations for Everyday and Seasonal Products Lory Ellebracht,
Jamie Netherton,
Casey Gentry		 10
NESUG 2011 A Comparison of PDLREG and GAM Procedures in Measuring Dynamic Effects Patralekha Bhattacharya 11
NESUG 2011 Dynamically Evolving Systems: Segmentation and Cluster Analysis Using Time David J. Corliss 11
NESUG 2011 Implementing a Customer Lifetime Value Framework in SAS Krishna Mehta 8
NESUG 2011 Using SAS GTL to Visualize Your Data when there is Too Much of it to Visualize Perry Watts,
Nathaniel Derby		 22
SGF 2011 Expanding PROC EXPAND Bruce F. Gilsen source 4
SGF 2011 Extending SAS High-Performance Forecasting Using User-Defined Models and External Forecasts Udo Sglavo source 9
SGF 2011 How to Customize Your Data Analysis with SAS OLAP Cube Calculations Tatyana Petrova source 22
SGF 2011 SAS/ETS and the Nobel Prize David A. Dickey source 14
SGF 2011 Testing the Adequacy of ARMA Models using a Weighted Portmanteau Test on the Residual Autocorrelations Thomas J. Fisher source 5
SGF 2011 Time Series Data Mining with SAS Enterprise Miner Sascha Schubert,
Taiyeong Lee		 source 12
NESUG 2010 Educational Outcome Analysis Using Maine's Wage Record Matching System Bruce H. Peel 10
NESUG 2010 Expanding PROC EXPAND Bruce F. Gilsen 4
NESUG 2010 Simulating Time Series Analysis Using SAS, Part III: Error Correction Model (ECM) Ismail E. Mohamed 7
WUSS 2010 Graphing a Progression of Time Series Plots Nathaniel Derby source 9
MWSUG 2010 Using the JMP 9 R Interfaces to Perform Bayesian Analyses: Why, How, and What Dave LeBlond 18
SESUG 2010 Stationarity Testing in High Frequency Seasonal Time Series David A. Dickey source 10
SGF 2010 Adding Statistical Functionality to the DATA Step with PROC FCMP Stacey M. Christian,
Jacques Rioux		 source
zip		 13
SGF 2010 An In-House SAS Procedure to Balance Time Series: The TSRAKING Procedure Joana Berube,
Susie Fortier		 source 10
SGF 2010 Applications of PROC ESM in SAS 9.2 Anders Milhøj source 11
SGF 2010 Building Latent Growth Models Using PROC CALIS: A Structural Equation Modeling Approach Teck Kiang Tan,
Trivina Kang,
David Hogan		 source 19
SGF 2010 Determining Optimal Cash Allocation at ICICI Bank Branches with SAS Enterprise Guide and SAS/OR Software Sandipan Ray source 13
SGF 2010 Financial Analysis Using SAS PROCs Somaye Gharibvand,
Lida Gharibvand		 source 7
MWSUG 2009 Time Series Analysis 101: an introduction using Base SAS and SAS STAT David J. Corliss 7
PNWSUG 2009 A Simple Time Series Macro Scott Hanson 7
PNWSUG 2009 SAS Proc STATESPACE and the forecasting of Bureau of Labor Statistics JOLT and Diffusion Index Martin B. Jetton 13
NESUG 2009 Why We Need a Bayesian Approach to Early Detection of Epidemic Outbreaks and Financial Bubbles Using First-Order Autoregressive Models with Structural Changes Ernest S. Shtatland,
Timur Shtatland		 12
WUSS 2009 Application of Segmented Regression Analysis to the Kaiser Permanente Colorado Critical Drug Interaction Program Nikki M. Carroll source 8
WUSS 2009 PROC NLP Approach for Optimal Exponential Smoothing Srihari Jaganathan source 9
SGF 2009 An Analysis of Market Shares on the Danish Alcohol Market Using Unobserved Components Anders Milhøj source 10
SGF 2009 BioSense and the Federated Data Environment Russell Gann source 31
SGF 2009 Manipulating OLAP Cubes: Advanced Techniques for SAS Programmers Rupinder Dhillon,
Harry Droogendyk		 source 24
SGF 2009 Model Fitting and Data Analyses in SAS/ETS Software Using ODS Statistical Graphics Jan Chvosta,
Mark Little		 source 14
SGF 2009 Simulating Time Series Analysis Using SAS - Part I The Augmented Dickey-Fuller (ADF) Test Ismail E. Mohamed source 7
SGF 2009 Simulating Time Series Analysis Using SAS - Part II Cointegration Ismail E. Mohamed source 8
SGF 2009 Structural Analysis of Time Series Using the SAS/ETS UCM Procedure Rajesh S. Selukar source 13
WUSS 2008 Application of Segmented Regression Analysis to the Kaiser Permanente Colorado Critical Drug Interaction Program Nikki M. Carroll source 8
WUSS 2008 Combined Line - Double Bubbles - Pie chart Alexandre Zolotovitski source 5
WUSS 2008 Comparing efficiency of cross validated partial least squares regression and ridge regression models in predicting spatial variability of total nitrogen concentration in Truckee River, Nevada. Anpalaki J. Ragavan source 13
WUSS 2008 Using Unobserved Components Model (UCM) for a Stock Price Fluctuation Lida Gharibvand source 7
SESUG 2008 Biosurveillance and the Holy Grid - Does it Compute? Russell Gann source 41
SESUG 2008 Non Linear Programming Of Time Series Data To Minimize Eutrophication In Truckee River, Nevada Anpalaki J. Ragavan source 13
SESUG 2008 SAS Stat Studio: A Programming Environment for High-End Data Analysts Rick Wicklin source 19
SESUG 2008 Time Series Analysis with SAS and R Samuel T. Croker source 9
PHUSE EU 2008 Drug Safety Reporting - now and then David J. Garbutt source 23
MWSUG 2008 SAS Stat Studio: A Programming Environment for High-End Data Analysts Rick Wicklin 19
PNWSUG 2008 SAS Stat Studio: A Programming Environment for High-End Data Analysts Maura E. Stokes 19
NESUG 2008 Early Detection of Epidemic Outbreaks and Financial Bubbles Using Autoregressive Models with Structural Changes Ernest S. Shtatland,
Timur Shtatland		 15
NESUG 2008 Time Series Analysis Using SAS - Part I - The Augmented Dickey Fuller (ADF) Test Ismail E. Mohamed 6
NESUG 2008 Time Series Analysis with SAS and R Samuel T. Croker 9
SGF 2008 An Interpretation of Sparkline Graphs and Their Creation with SAS Software Paul OldenKamp source 7
SGF 2008 Another Look at Low-Order Autoregressive Models in Early Detection of Epidemic Outbreaks and Explosive Behaviors in Economic and Financial Time Series Ernest S. Shtatland source 12
SGF 2008 Computational Algorithm for Estimation of Panel Data Models with Two Fixed Effects Alan Ricardo da Silva,
Patrick F. Alves		 source 10
SGF 2008 Data Mining Application of Non-Linear Mixed Modeling in Water Quality Analysis Anpalaki J. Ragavan source 14
SGF 2008 Easy Rolling Statistics with PROC EXPAND Premal P. Vora source 6
SGF 2008 Integrating Consumer Demand to Improve Shipment Forecasts Charles Chase source 10
SGF 2008 Making Sense of Multi-Core Processor Technology for the SAS Environment Carl E. Ralston source 9
SGF 2008 SAS Stat Studio: A Programming Environment for High-End Data Analysts Rick Wicklin source 19
SGF 2008 Text and Data Mining to Investigate Expenditures on Prescribed Medicines Guoxin Tang source 7
SGF 2008 The Early Warning Project: Prewarning and Avoiding Problems and Costly Downtime in Complex Industrial Processes Torulf Mollestad,
Frode Oplenskedal		 source 12
NESUG 2007 Automated Real-Time Forecasting of Stream Conditions with SAS Samuel T. Croker,
Shane L. Hornibrook,
Tomonori Ishikawa		 10
NESUG 2007 Low-Order Autoregressive Models in Early Detection of Epidemic Out-breaks and Explosive Behaviors in Economic and Financial Time Series Ernest S. Shtatland 10
NESUG 2007 PROC EXPAND to the Rescue! Premal Vora 5
NESUG 2007 Resampling Census Data for Survey Data Analysis Adeline J. Wilcox 10
NESUG 2007 SAS, Econometrics, and Computation Speed Michael Boldin 12
SESUG 2007 A Study on Kentucky Highway Fatalities Highway Fatalities Ryan Glassford source 5
SESUG 2007 Automated Real-Time Forecasting of Stream Conditions with SAS Samuel T. Croker,
Shane L. Hornibrook,
Tomonori Ishikawa		 source 9
SESUG 2007 Data Mining and Investigating Treatment Options of Osteomyelitis with MRSA Hamed Zahedi source 9
SESUG 2007 Data Mining Episode Groupers Patricia B. Cerrito source 13
SESUG 2007 Maryland Region Meteorologically Adjusted Ground-Level Ozone Trend Analysis Ozone Trend source 16
SESUG 2007 PROC TIMEPLOT - An Old Way to Plot New Data James W. Terry source 6
SESUG 2007 USE OF ARIMA TIME SERIES AND REGRESSORS TO FORECAST THE SALE OF ELECTRICITY Beatrice Ugiliweneza source 11
SESUG 2007 Yankees and Red Sox: A Time Series Analysis of Win Percentage Correlations between Professionals Baseball Teams source 11
MWSUG 2007 A Macro for Producing Graphs used in Assessing a Spectrum David W. Meek 6
WUSS 2007 Data Mining Using SAS Enterprise Miner Randall Matignon source 10
WUSS 2007 Time Series Cross Sectional Analysis of Total Nitrogen Concentration in Truckee River, Nevada Using SAS Anpalaki J. Ragavan source 11
SGF 2007 Analyzing Time Series Cross-Sectional Data with the PANEL Procedure Jan Chvosta,
Donald Erdman		 source 11
SGF 2007 Best Practices for Implementing a BI Strategy with SAS Mike Varney,
Brian Vanderlinden		 source 10
SGF 2007 Customer Case Study: SAS Application in a Deregulated Electric Retailer Ernest L. Podraza source 4
SGF 2007 Data Mining to Investigate the Prescribing of Medications Longitudinally Mussie A. Tesfamicael source 17
SGF 2007 Forecasting Method: An Overview of Models and Techniques David A. Dickey source 17
SGF 2007 OLS Regression? Auto-Regression? Dynamic Regression? Rodger Zhang source 12
SESUG 2006 Comparing Time series, Generalized Linear Models and Artificial Neural Network Models for Transactional Data Analysis Joseph Twagilimana source 9
SESUG 2006 Effective Forecast Visualization With SAS/GRAPH Effective Forecast Visualization source 12
SESUG 2006 ST09 Application of the Generalized Linear Model to the Prediction of Lung Cancer Survival Andrew Karem source 18
WUSS 2006 Detecting Structural Change Using SAS ETS Procedures Archie J. Calise,
Joseph E. Earley		 source 7
WUSS 2006 Real-Time Sales Volumes Projection with SAS - A Challenge in Implementing a Data-Based Solution in the Automobile Industry Keiko I. Powers source 8
SUGI 2006 Biosurveillance and Outbreak Detection Using the ARIMA and LOGISTIC Procedures Ernest S. Shtatland source 8
SUGI 2006 Data and Text Mining the Electronic Medical Record to Improve Care and to Lower Costs Patricia B. Cerrito,
John C. Cerrito		 source 20
SUGI 2006 Introduction to SAS Enterprise Guide 4.1 for Statistical Analysis Charles B. Hallahan,
Linda P. Atkinson		 source 22
SUGI 2006 Litigation Data Analysis/Auditing/ETL for BI: Triplets Separated at Birth Nicholson E. Warman source 15
SUGI 2006 Modeling Water Quality Trend in Long Term Time Series Anpalaki J. Ragavan,
George C. J. Fernandez		 source 10
SUGI 2006 Moving SAS Solutions to a Production IT Environment Mike Miller,
David Simpson		 source 10
MWSUG 2005 Mining Transactional And Time Series Data Michael J. Leonard 26
MWSUG 2005 Time Dependent Data Exploration And Preprocessing: Doing It All By SAS Joseph Twagilimana 10
WUSS 2005 A Journey to Ellis Island: Profiling Historical Immigration Using SAS and JMP Time Series Methods Archie J. Calise,
Joseph E. Earley		 source 6
WUSS 2005 Effects of PROC EXPAND Data Interpolation on Time Series Modeling when the Data are Volatile or Complex Keiko I. Powers source 7
NESUG 2005 An Introduction to Wavelet Analysis with SAS Michael Lane 10
NESUG 2005 Using SAS for Cointegration and Error Correction Mechanism Approaches: Estimating a Capital Asset Pricing Model for House Price Returns Ismail E. Mohamed,
Theresa R. DiVenti		 14
SUGI 2005 A Shift in Time: Using SAS Date Alignment Operators Andrew H. Karp source 2
SUGI 2005 Comparing the SAS Forecasting System with PROC HPF and SAS Enterprise Miner Patricia B. Cerrito source 9
SUGI 2005 Introducing SAS Forecast Studio Michael J. Leonard,
Brenda Wolfe,
Paddy Fahey		 source 16
SUGI 2005 Litigation and SAS: Some Dos and Don'ts (or, You Call that Evidence?) Nicholson E. Warman source 10
SUGI 2005 Mining Transactional And Time Series Data Michael J. Leonard,
Brenda Wolfe		 source 26
SUGI 2005 Stationarity Issues in Time Series Models David A. Dickey source 17
SUGI 2005 Using SAS to Detect Errors in X12-Arima Seasonal Adjustment Nicole D. Brooks source 3
NESUG 2004 An Animated Guide: Proc UCM Russell M. Lavery 23
SESUG 2004 Case Studies in Time Series David A. Dickey source 10
SESUG 2004 Case Studies in Time Series: Periodic Behavior and Related Issues Periodic Behavior,
Related Issues,
David A. Dickey		 source 16
WUSS 2004 Alternative Seasonality Detectors Using SAS /ETS Procedures Joseph E. Earley source 6
WUSS 2004 Empirical Investigation of Time Series Frequency Conversion with PROC EXPAND Keiko I. Powers source 9
WUSS 2004 Time Series Magic: Using PROC EXPAND with Time Series Data Andrew H. Karp source 8
WUSS 2004 Working with SAS Date and Time Functions Andrew H. Karp source 12
PNWSUG 2004 Working with SAS Date and Time Functions [presentation] Andrew H. Karp 70
SUGI 2004 Case Studies in Time Series II: Periodic Behavior and Related Topics David A. Dickey source 17
SUGI 2004 DB2, SAS, and You Robert Ellsworth source 5
SUGI 2004 Improved Methods for Early Fault Detection in Enterprise Computing Servers Using SAS Tools Kenny C. Gross,
Kesari Mishra		 source 10
WUSS 2003 Advanced Analytics with Enterprise Guide Catherine Truxillo,
Stephen McDaniel		 source 9
WUSS 2003 Using PROC EXPAND with Time Series Data Andrew H. Karp source 7
SESUG 2003 Missing Data Values: Analyzing their Effects on Rainfall Forecasts Using PROC EXPAND and the SAS Time-Series Forecasting System Richard A. March source 4
SESUG 2003 Working with SAS Date and Time Functions Andrew H. Karp source 9
MWSUG 2003 Working with SAS Data and Time Functions Andrew H. Karp 9
NESUG 2003 Basic Usage of SAS/ETS' & SAS/STAT' to Forecast Time Series Douglas L. McAllaster 10
NESUG 2003 Developing Custom Analytic Tasks for Enterprise Guide Joe Carter,
Stephen McDaniel,
Mike Porter		 6
NESUG 2003 Using Cluster Analysis for Retail Portfolio Segmentation in an Economic Capital Model: Homogeneity by Common Default Behavior Over Time Shannon Kelly 12
SEUGI 2003 Data Modelling in SAS - How SAS is Used for Research and Teaching to Enable Students to Become More Marketable [presentation] Iveta Stankovicova source 30
SEUGI 2003 Demand-Driven Strategies for Increased Profitability: SAS Demand Intelligence (Part 2) [presentation] Udo Sglavo source 25
SEUGI 2003 How SAS is Used for Research and Teaching to Enable Students to Become More Marketable [presentation] Iveta Stankovicova source 22
SEUGI 2003 Managing Installation and Migration in SAS 9.1 - an overview [presentation] Achim Granzen source 34
SEUGI 2003 SAS Supply Chain Intelligence - Or how to manage the Flood [presentation] Gerhard Held source 37
SEUGI 2003 Short-term forecasts for freight transportation planning in the Ministry of Russian Railways [presentation] Elena Kounaeva,
Sergy Bezbogov		 source 16
PharmaSUG 2003 Benchmarking Forecasting Practices in the Pharmaceutical Industry Chaman L. Jain,
St. John's		 6
SUGI 2003 Application of the LOESS Procedure for Monitoring and Detecting Critical Movements in the US Automobile Market Keiko I. Powers,
J. Michael Jay,
Tie Gao		 source 6
SUGI 2003 Case Studies in Time Series David A. Dickey source 9
SUGI 2003 eveloping Custom Analytic Tasks for SAS Joe Carter,
Stephen McDaniel,
Mike Porter		 source 6
SUGI 2003 Transactional Records Access Clearinghouse: SAS Based Warehouse and Mining Tools Keeps Tabs on U.S. Government Susan B. Long,
Linda Roberge,
Jeffrey T. Lamicela		 source 6
NESUG 2002 Estimating Confidence Intervals Around Relative Changes in Outcomes in Segmented Regression Analyses of Time Series Data Fang Zhang,
Anita Wagner,
Stephen B. Soumerai,
Dennis Ross-Degnan		 7
NESUG 2002 Forecasting with the Time Series Forecasting System in SAS/ETS Charles B. Hallahan 6
NESUG 2002 Temporal Optimization: Convergence of Time Series and Linear Modeling for Selecting Portfolio Strategies Haftan M. Eckholdt 3
SESUG 2002 Basic Usage of SAS/ETS Software to Forecast a Time Series Douglas L. McAllaster source 10
SESUG 2002 The Lag-o-Matic: An Improved Method for Selecting the Lag Structure of Multiple Predictor Variables in the Absence of Theory David C. Sharp,
Stephen M. Finnigan		 source 5
WUSS 2002 Comparison of Several SAS Approaches to Mean Imputation for Time Series Data with Missing Data Points Keiko I. Powers source 4
WUSS 2002 Seasonality Detectioh in the Energy Sector Using the SAS System Joseph E. Earley,
Seid M. Zekavat		 source 3
SEUGI 2002 Corporate Financial & Operational Analytical and Reporting System [presentation] Elias Soloviev,
Eugene Okhovski		 source 43
SEUGI 2002 Developing an infrastructure for the Efficient Use of SAS at the Federal Statistical Office Germany [presentation] Heinz Stralla source 21
SEUGI 2002 Enterprise Guide - A Gateway to SAS [presentation] Amarpal Brar source 18
SEUGI 2002 Market risk estimation through modeling and visualizations in the SAS System [presentation] Jerzy Krawczuk source 9
SEUGI 2002 The problem of treasurey portfolio optimisation [presentation] Alexey Kulemin,
Vasily Konuzin,
Vasily Sorokoumov,
Victor Kulyshev		 source 52
SUGI 2002 Neural Networks and Genetic Algorithms as Tools for Forecasting Demand in Consumer Durables Jerry Nickelsburg,
Paul D. McNelis		 source 6
MWSUG 2001 Working with SAS Date and Time Functions Andrew H. Karp 7
NESUG 2001 The Time Series Forecasting System Charles B. Hallahan 6
WUSS 2001 Detecting Seasonality in Univariate Time Series Data Using the SAS System Joseph E. Earley,
Seid M. Zekavat		 source 6
SESUG 2001 Use of SAS/ETS and the BLS-Census Data Ferret for the Comprehensive Everglades Restoration Program Richard A. March source 7
SCSUG 2001 Use of SAS/ETS and the BLS-Census Data Ferret for Comprehensive Everglades Restoration Program Richard A. March 7
SEUGI 2001 A web interface for portfolio risk optimisation with SAS System Giuseppe Marcon,
Maria Rita Pepe		 source 14
SEUGI 2001 Constructing a time series using PROC SUMMARY and a multi-label format [presentation] Hans Thomsen source 23
SEUGI 2001 Evolution of the Data Warehouse at the Russian Railways [presentation] Igor Movchikov source 24
SEUGI 2001 New Features and Future Directions for Enterprise Miner [presentation] David R. Duling,
Gerhard Held		 source 31
SEUGI 2001 New Visualisation in 8.2 [presentation] Stuart A. Nisbet source 32
SEUGI 2001 The Use of Enterprise Miner with Large Volumes of Data, for Forecasting in an Automated Batch Process [presentation] Justine Eastman source 12
PharmaSUG 2001 New Visualization in V8.2 Himesh Patel 8
SUGI 2001 Dynamic Ad-Hoc Reporting via the Web: Real-World Comparison of MDDB Report Viewer and AppDev Studio Colin J. Harris source 10
SUGI 2001 Migrate to Oracle? I Need My SAS!! Dianne Louise Rhodes source 5
SUGI 2001 New Visualization in V8.2 Himesh Patel source 7
SUGI 2001 The Spectrum of Broadway: A SAS PROC SPECTRA Inquiry Joseph E. Earley,
James D. Ryan		 source 5
SCSUG 2000 Using JMP Version 4 for Time Series Analysis William R. Gjertsen 10
SESUG 2000 Using JMP Version 4 for Time Series Analysis William R. Gjertsen source 10
NESUG 2000 Point & Click Forecasting with the Time Series Forecasting System Charles B. Hallahan 9
NESUG 2000 Working with SAS Date and Time Functions Andrew H. Karp 7
WUSS 2000 SAS STAT applications in Econometrics Mathura Thillainathan,
George C. J. Fernandez		 source 10
WUSS 2000 Visiting the White House with SAS: A PROC SPECTRA Application Joseph E. Earley source 5
SEUGI 2000 Enterprise Guide Version 1.1 [presentation] Adrian Bruty,
Carol Williams Rigsbee		 source 19
SEUGI 2000 Euro Blue Chips Index - A new benchmark for European Stock Markets [presentation] Emiliano Laruccia,
Marcello Esposito,
Stefania Carpi		 source 33
SEUGI 2000 Web Enabling A Large Data Warehouse Clare Somerville,
Colin J. Harris		 source 11
SUGI 2000 Cinema and Seasonality: A SAS System PROC X11 Application Joseph E. Earley,
Jia L. Wang		 source 6
SUGI 2000 SAS Programs to Get the Most from X-12-ARIMA's Modeling and Seasonal Adjustment Diagnostics Catherine C. Hood source 6
SUGI 2000 The Time Series Forecasting System Charles B. Hallahan source 9
SUGI 2000 The Use of Kernel Density Estimators to Monitor Protocol Compliance Patricia B. Cerrito,
George R. Barnes		 source
WUSS 1999 Forecasting Geographic Data Michael J. Leonard,
Renee Samy		 source 7
WUSS 1999 Investigating Seasonality in BLS Data Using PROC ARIMA Joseph E. Earley source 6
WUSS 1999 Seasonal Trend Analysis of Monthly Water Quality Data Jie Tian,
George C. J. Fernandez		 source 6
WUSS 1999 Using PROC EXPAND with Time Series Data Andrew H. Karp source 4
WUSS 1999 Working with SAS Date and Time Functions Andrew H. Karp source 8
MWSUG 1999 Multivariate Time Series Analysis - An adaptation of Box-Jenkins Methodology Joseph N. Ladalla 6
MWSUG 1999 Working with SAS Date and Time Functions with Reference to Year 2000 Issues Andrew H. Karp 7
SEUGI 1999 Exploiting data warehouse metadata for knowledge management [presentation] Berthold Weismann source 27
SEUGI 1999 Forecasting Cross-Sectional Time Series: A Data Mining Approach Using Enterprise Miner Software John C. Brocklebank,
Michael Leonard,
Taiyeong Lee		 source 3
SEUGI 1999 Outlier detection at EUROSTAT [presentation] Pacal Loosveldt source 31
SEUGI 1999 Risk data warehousing: leveraging operational gains [presentation] Pankaj Mistry source 23
SEUGI 1999 S.O.C.R.A.T.E.S. Simultaneous Optimal Control by Recursive and Adaptive Estimation Systsem Giacomo Patrizi source 12
SUGI 1999 Autoregressive Integrated Moving Average Models for Comparing Forecasted to Actual Values of CPU Workloads for Open Systems Anthony C. Waclawski source 10
SUGI 1999 Forecasting Cross-Sectional Time Series: A Data Mining Approach Using Enterprise Miner Software John C. Brocklebank,
Michael Leonard,
Taiyeong Lee		 source 3
SUGI 1999 From Prediction to Validation: Who Understands the Past, Controls the Future (Time Series) Edward Aronov source 4
SUGI 1999 Large Scale Data Warehousing with the SAS System Tony Brown,
Leigh A. Ihnen,
Jim Craig		 source 10
SUGI 1999 Simulation and Estimation of Fractionally Integrated Time Series Jeffrey S. Butler source 6
SUGI 1999 The Time Series Forecasting System Charles B. Hallahan,
Renee Samy		 source 9
SUGI 1999 Web Enabling a Large Data Warehouse: Improved Metadata for Expert Analysts and Wider Access to Management Information Clare Somerville,
Colin J. Harris		 source 10
SUGI 1999 Working with SAS Date and Time Functions Andrew H. Karp source 7
WUSS 1998 Analysis of the Multivariate ENSO Index Using SAS/ETS Procedures Joseph E. Earley source 4
WUSS 1998 Using PROC VARCLUS to Examine Geographical Patterns in Biological Time Series Data Along the California Coast Stephen Schroeter,
John Dixon,
Richard O. Smith		 source 4
WUSS 1998 Working with SAS Date and Time Functions Andrew H. Karp source 7
NESUG 1998 Geostatistics Using the SAS System A. Katherine Ricci 5
NESUG 1998 Option Pricing: A Time Series Alternative to Black-Scholes David R. Roberts 7
NESUG 1998 Working with SAS Date and Time Functions With Reference to Year 2000 Andrew H. Karp 8
SESUG 1998 Regression with Time Series Errors David A. Dickey 9
SESUG 1998 X-12-Graph: Visual Diagnostics for Time Series Modeling and Seasonal Adjustment Catherine C. Hood. U.S 6
PNWSUG 1998 Using PROC EXPAND with Time Series Data Andrew H. Karp 4
PNWSUG 1998 Working with SAS Date and Time Funcitons Andrew H. Karp 8
SEUGI 1998 Data Mining at IMS America: How We Turned a Mountain of Data into a Few Information-rich Molehills Jerry Kagan,
Paul Kallukaran		 source 7
SEUGI 1998 Data warehouse as an organizational tool in the Institute for Tourism Blazenka Vrdoljak-Salamon,
Zrinka Marusic		 source 11
SEUGI 1998 Module for the Central Bank Analysis of Economic Situation of Enterprises Piotr Boguszewski source 13
SEUGI 1998 Statistical database concept implemented in Oracle and automatisation of proceedings for Bank of Slovenia using the SAS System Andrej Navodnik,
Irena Komprej		 source 4
SEUGI 1998 Using SAS software in developing the regional economy and finance analysis and forecasting system Egor Liptchinski,
Maxim Emelenko		 source 8
SUGI 1998 Moving Data Between SAS and FAME Stephen B. Taubman source 2
SUGI 1998 Using Macros to Produce Multiple Time Series Graphs Kimberly S. Blair source 5
SUGI 1998 Working with SAS Date and Time Functions Andrew H. Karp source 7
SCSUG 1997 An Application of Cycle Regression Analysis Algorithm to Predict Electric Utility Demand Mayur R. Mehta,
Walter E. Johnston		 7
WUSS 1997 A Fast and Robust Method for Pattern Matching in Time Series Databases Eamonn Keogh source 6
WUSS 1997 Analysis of Time Series Data - An Application in Health Care Sujaya Parthasarathy source 6
WUSS 1997 Working with SAS Date and Time Functions Andrew H. Karp source 7
NESUG 1997 A New Adaptive Model for Prediction With the Time Series Edward Aronov 9
NESUG 1997 Attribute Smoothing: A Pattern Forecasting Technique David R. Roberts 4
NESUG 1997 Data Mining at IMS America: How We Turned a Mountain of Data into a Few Information-rich Molehills Paul Kallukaran 8
NESUG 1997 Time Series Magic: Smoothing, Interpolating, Expanding and Collapsing Time Series Data With PROC EXPAND Andrew H. Karp 5
MWSUG 1997 Examining Cointegration Among Time-Series Variables Using Customized SAS Macro: Residual-Based Methods Jun Zuo 8
MWSUG 1997 Working with SAS Date and Time Functions Andrew H. Karp 7
SESUG 1997 Identifying the Order of Integration of Time-series Data Using Customized SAS Macros: Dickey-Fuller and Augmented Dickey-Fuller Tests Jun Zuo 6
SEUGI 1997 A system for managing economic databases Helena Pompushko source 6
SEUGI 1997 Comparison between different methods to estimate orders in ARIMA models Dominique LADIRAY,
Michel Grun-Rehomme		 source 11
SEUGI 1997 Construction of a consumer confidence index with the X11 Procedure from SAS/ETS Hans Bay source 4
SEUGI 1997 Using SAS software to forecast the results of the Russian parliamentary and presidential elections Igor Romanov source 27
SUGI 1997 Forecasting an Electric Utility's CO2 Emissions Using SAS/AF and SAS/STAT Software: A Linear Analysis Azharul Islam,
David L. Wang		 source 5
NESUG 1996 Design and Development of the Census Burea's Time Series Analysis Repository Danielle Ringstrom 9
NESUG 1996 SAS Printout in Chinese Jin Pihuan,
Chen Chunwei		 2
MWSUG 1996 Detecting Changes in Mean of Correlated Data Tze-San Lee,
Lei Zhang		 4
WUSS 1996 Using PROC EXPAND with Time Series Data Andrew H. Karp source 4
SEUGI 1996 A product/customer profitability system based on a data warehouse Marcin Romanowski source 9
SEUGI 1996 ARIMA-model application for forecasting futures markets A. E. Smirnov,
S. V. Kutsev,
V. E. Sorokoumov		 source 4
SEUGI 1996 Computer-aided sales forecasting (CAS-FO) and the art of planning - a paradox? Thomas Schmidt-Melchiors,
Wolfgang Schum		 source 12
SEUGI 1996 The South African Breweries sales forecasting system: from data to planning information Kenneth Carden source 10
SUGI 1996 Exploring Economic Time Series with PROC ARIMA Joseph E. Earley source 4
SUGI 1996 Teaching the SAS System as an Academic Subject Andrew H. Karp source
SUGI 1996 Temporal and Geographical Statistical Modeling: A New Paradigm M. W. Hemphill,
Thomas W. Sager		 source 9
SUGI 1996 Unbalanced Panel Data Estimation Using SAS/lML Software N. Clay Greene,
John Ah-Sen		 source 3
SUGI 1996 Working with SAS Date and Time Functions Andrew H. Karp source 5
SCSUG 1995 Advanced Analysis of Stock Prices Using the CRSP Tapes and SAS: Protocols for Both Academic Research and Classroom Use Glenn Millard,
Garland Simmons		 20
NESUG 1995 Estimation of Nonlinear Models: A Computational Review D. Das Purkayastha 8
NESUG 1995 Repetitive Data Retrieval from Time-Series Data Robert Charles Oshinsky 2
NESUG 1995 Using PROC EXPAND with Time Series Data Andrew H. Karp 4
NESUG 1995 Working with SAS Date and Time Functions Andrew H. Karp 5
WUSS 1995 An Introduction to PROC ARIMA Using Macroeconomic Time Series Joseph E. Earley source 14
WUSS 1995 Detecting Singularity of a Matrix and Adjustment for Positive Definite Matrix Using Cholesky Decomposition Theorem - SAS/IML Jianmin Liu source 6
SESUG 1995 Using PROC EXPAND with Time Series Data Andrew H. Karp 4
SESUG 1995 Working with SAS Date and Time Functions Andrew H. Karp 5
SEUGI 1995 APPS - a 5th Generation Sales Planning and Forecasting System Sven Viergutz source 12
SEUGI 1995 UBIRIS - A System to Support Investment Research and Publications at UBS Beat Moser source 10
SEUGI 1995 Using the SAS System to Acquire a Set of Golden Ten Orbits from Two Populations Hans de Vos source 12
SEUGI 1995 Wouldn't it be Good if we Understood what Drives our Claims Kevin Williams source 9
SUGI 1995 Demand Forecasting: Do You Know Where Your Products Are Going? Robin Reese,
D'Arcy Dittmer,
Daphne McCarley,
Don Waddell		 source 4
SUGI 1995 Using the SAS System for Market Research Laurie Rose source 5
WUSS 1994 A Reassessment of the Monetary Approach to Exchange Rate Determination: A Multivariate Analysis of Difference-Stationary Time Series Victor Gastnaga source 6
WUSS 1994 Working with SAS Date and Time Functions Andrew H. Karp source 5
NESUG 1994 Development of an Adaptive Model for Forecasting of Nonstationary Processes Edward Aronov 9
NESUG 1994 Macros for Working with Nonstationary Time Series Ashok Mehta 9
NESUG 1994 PROC DATASOURCE - Strategies for User Support Sharon J. O'Donnell 6
SESUG 1994 Forecasting Time Series Data with the SAS System for Information Delivery Andrew H. Karp 3
SEUGI 1994 Designing a Management Workbench for Top Management at Deutsche Bank AG Elke Haaren-Retagne source 3
SEUGI 1994 Forecasting the Cost of Corporation Tax Changes Over a Three Year Cycle Michael Molloy source 4
SUGI 1994 Exploring Broadway with SAS/ETS: A Statistical Analysis of the Acting Profession Joseph E. Earley,
James D. Ryan,
Archie J. Calise		 source 3
SUGI 1994 Managing Large Financial Data with Ease: CRSP, COMPUSTAT, Etc., with SAS Paul J. Ratnaraj,
Carol M. Katzman		 source 5
SUGI 1994 Nonlinear Regression Analysis and Nonlinear Simulation Models Donald Erdman,
Mark Little		 source 9
SUGI 1993 Forecasting Methods Mark Little source 13
SUGI 1993 Forecasting the Volatility of Financial Markets: ARCH/GARCH Models and the AUTOREG Procedure Minbo Kim source
SUGI 1993 SAS System Visual Performance in Evaluating Arrhythmia Time Series B.J. Cerimele source 3
SUGI 1993 The Laboratory Review System: A SAS-based Graphical and Statistical Tool Developed for a Computer-Assisted New Drug Application (CANDA) Submission Russell R. Holmes,
David A. Bright		 source 6
SESUG 1993 Developing an In-House SAS Training Program for an Academic Environment Barbara B. Okerson 5
SCSUG 1992 Using PROC PRINTTO Thomas J. Winn Jr. 8
NESUG 1992 More on Business Forecasting With SAS Jeffrey Jarrett 5
NESUG 1992 The Laboratory Review Systems: A SAS-based Graphical and Statistical Tool Developed for a CANDA Submission Russell R. Holmes,
David A. Bright		 6
SEUGI 1992 Analysing Business and Economic Data with SAS/ETS Software Georg Morsing source 9
SEUGI 1992 Automatic Forecasting Menu System Joachim Hefner source 11
SUGI 1992 A Supplemental SAS Function for Computing Moving Average Shi-Tao Yeh source 3
SUGI 1992 Analyzing Business and Economics Data with SAS/ETS Software Mark Little source 9
SUGI 1992 Testing the Rationality of Panel Data Forecasts Using a GMM Estimator Richard H. Cohen source 6
SUGI 1992 Weather Sensitive Appliance Load Curves: Conditional Demand Estimation Deepak A. Keshani,
Thomas N. Taylor		 source 9
NESUG 1991 Overview of ETS Procedures for Business Forecasting Jeffrey Jarrett 4
MWSUG 1991 Forecasting Exogenous Variables Using SAS PROC NLIN Galip Feyzioglu,
David L. Wang		 6
SEUGI 1991 Is EIS Easy? Jim Thomason source 5
SEUGI 1991 Statistical Evaluation and Forecasting of Steel Corrosion Data Bernhard Kienzler,
Emanuel Smailos,
Rainer Koester		 source 11
SUGI 1991 Load Data Analysis Workstation (LDAW): A SAS/AF Information Systems Application Burtt Blodgett,
Diane Bailey,
John Powers		 source 6
SUGI 1991 Uses of SAS Software for Implementation of SPC on Continuous Processes Robert V. Baxley Jr. source 7
SEUGI 1990 Directions of the SAS System in Statistics and Decision Support Gerhard Held source 7
SEUGI 1990 Distribution of Information with SAS Software Paul Erik Hansen,
Peter Hansen		 source 8
SEUGI 1990 Multivariate Outlier Detection Christian Derquenne source 9
SEUGI 1990 Short Term Predictions: A Monitoring System M. Helder source 7
SUGI 1990 CPU Load Forecasting Using the ARIMA Procedure Robert Hubata source 4
SUGI 1990 Determining Weight Values for EWMA Control Schemes Using the ARIMA Procedure John C. Brocklebank source 10
SUGI 1990 Transfer Function Model for Gloss Prediction of Coated Aluminum Using the ARIMA Procedure Mozammel H. Khan source 6
NESUG 1989 Adjusting Time Series Data Jim Wimbish 9
NESUG 1989 What You Can Expect With Release 6.06 of the SAS System Barbara H. Pendergrass 3
SEUGI 1989 Use of SAS/IML Software In Calculation of Certain Consumer Price Index Numbers Martin Gregory source 13
SUGI 1989 A Program to Calculate Weights for Specified Spectral Windows: A SPECTRA Procedure Application Tim Arnold,
Ed Fryar		 source 2
SUGI 1989 A Useful General Procedure File for the ARIMA Procedure Michael H. Dong,
Yi Tsong		 source 3
SUGI 1989 But Will it Sell? Market-based Decision Systems Using SAS Software Lee H. Evans source 9
SUGI 1989 Combining SAS/AFB SAS/FSP, and SAS/DMI Software to Specify Parameters for Batch Jobs and Submit Them Catherine C. FitzGerald source 4
SUGI 1989 Estimating Stochastic Coefficient Models with the SAS System Charles B. Hallahan source 6
SUGI 1989 How to Establish a Forecasting System with SASSoftware Joel Fingerman source 10
SUGI 1989 Most Creative Use of the Software-Monochrome Leslie Worf source 116
SUGI 1989 SAS/ETS Software: A Report on the New. Features in Release 6.03 and Other Work in Progress Mark Little source 4
NESUG 1988 Using SAS/ETS Software for Instruction and Research at Pace University Gerry Pauline,
Walter Morris		 5
SEUGI 1988 Lovmodel, Overview of the Danish Law Model System Hans Hansen source 28
SUGI 1988 Forecasting the Economy Using the Composite Leading Index, Its Components, and a Rational Expectations Alternative Lung-ho Lin,
Steven C. Myers		 source 6
SUGI 1988 The Influence of Economic Variables on Seminary Participation: A SAS/ETS Application Archie J. Calise,
Joseph E. Earley		 source 5
SUGI 1988 Time-Series Investigation of Anomalous Thermocouple Responses in a Liquid-Metal-Cooled Reactor Kenny C. Gross,
H. Pete Planchon,
J. Poloncsik		 source 4
SUGI 1988 Workload and Revenue Projection for Computer Center Cost Recovery Systems Tim Carrico,
Nada Harris		 source 9
SEUGI 1987 A Macro for Weighted Moving Averages Leena Metso source 4
SUGI 1987 A SAS/ETS Software Forecasting and Inventory Planning System David Brauer,
Patrick Cardamone		 source 6
SUGI 1987 Application of Intervention Analysis to Power Plant Monitoring Data Linda E. Bireley source 9
SUGI 1987 Comparison of Four Univariate Methods for Forecasting Seasonal Data by the SAS System Jeffrey Jarrett source 5
SUGI 1987 Forming SAS Time Series Data Sets from the International Financial Statistics Data Tape of the International Monetary Fund Alex Anckonie III source 6
SUGI 1987 Seasonal Adjustment Operations of Canadian Socio-Economic Time Series Estela Bee Dagum,
Misako Grafton		 source 5
SUGI 1987 The Evolution of a Plot Chris Potter source 5
SUGI 1987 Time Series Intervention Analysis Using SAS Software Terry J. Woodfield source 9
SUGI 1987 Using SAS Software to Pass Data to IBM's Graphical Data Display Manager Rameshwar Ramotar source 5
SUGI 1986 Checking for Autocorrelation in Regression Residuals John C. Brocklebank,
David A. Dickey		 source 7
SUGI 1986 Inference from the Incomplete Longitudinal Design: A Collection of SAS Macros James Rochon source 6
SUGI 1986 Interfacing SAS Software with the B34S System Recursive Residual Option: A Brief Look at Theory and an Example Houston H. Stokes source 6
SUGI 1986 Performing the X1 1ARIMA Seasonal Adjustment John C. Brocklebank,
David A. Dickey		 source 10
SUGI 1986 Use of SAS Software to Forecast Claims R. Choudary Hanumara,
Michael Salzillo		 source 6
SUGI 1986 Using PROC NLIN for Time Series Prediction Wayne Fuller source 6
SEUGI 1985 New Features of the SAS/ETS and SAS/OR Software in Version 5 John C. Brocklebank source 37
SUGI 1985 A Time Series Approach to Modeling Daily Peak Electricity Demands Michael F. Jacob source 6
SUGI 1985 Applications in Bayesian Analysis Arnold Zellner source 7
SUGI 1985 Changes and Enhancements to SAS/ETSSoftware David M. DeLong,
Leigh A. Ihnen,
Mark Little		 source 12
SUGI 1985 Estimating Autocorrelations and Crosscorrelations where Missing Values are Present: A SAS Macro Pan-Yu Lai,
Kenneth M. Portier		 source 5
SUGI 1985 Selection of Variables for Identification of Transfer Function Models on SAS Software James A. Deddens,
Wang Ping		 source 6
SUGI 1985 Two-way Communication Between SAS Software and the SCA Statistical System: The LINKSCA and SCALINK Procedures Lon-Mu Liu,
Houston H. Stokes		 source 6
SEUGI 1984 Basing an Economic Information System on SAS Martin Harnqvist source 7
SEUGI 1984 New Statistical Features in SAS Gerhard Held source 13
SEUGI 1984 Solving Statistical Problems Using SAS and TPL Together Manuel Angel Santos,
Teofilo Valdes		 source 7
SUGI 1984 Applying Pattern Recognition to Validating Time Series Data for Electric Utility Load Research Andrew E. Allen,
Tom L. Johnston,
Edward L. Tabakin		 source 6
SUGI 1984 Changes and Enhancements to SAS/ETS Procedures David M. DeLong,
Leigh A. Ihnen,
Mark Little		 source 6
SUGI 1984 Interactive SAS Programming Harriet E. Brichta source 6
SUGI 1984 Interfacing SAS Software with the SCA System: the SCALINK Procedure Lon-Mu Liu,
Houston H. Stokes		 source 6
SUGI 1984 On the Limitations of Akaike's Information Criterion and Its Use in PROC STATESPACE Jim Chavern source 6
SUGI 1984 Predicting Prison Population With the SAS/ETS Product Steven P. Davis source 6
SUGI 1984 Preliminary Transformations in Time Series Modeling John C. Brocklebank,
David A. Dickey		 source 6
SUGI 1984 Residential Energy Forecasting: A Pragmatic Application of Box-Jenkins Michael F. Jacob source 6
SEUGI 1983 SAS Applied to Statistical Databanks via a Command Language Inger Nilsson 6
SEUGI 1983 SAS as part of a Marketing Information System Peter Buete 16
SUGI 1983 An Algorithm for Producing Exact Maximum Likelihood Estimates for an ARIMA(p,q) Process Carol M. Reilly source 3
SUGI 1983 Interactive Routines for Handling Time Series Data on SAS CMS John D. Friedmann source 5
SUGI 1983 Living with the AHA: The Construction of a Multi-Year Hospital Information Data Base Using the AHA Annual Survey and SAS Mireille Leger,
Frederick E. Pratter		 source
SUGI 1983 Offense, Defense, and Causality in Baseball Charles F. Hofacker source 5
SUGI 1983 SAS: A Decision Support System for Management Raymond A. Gibley,
Heidi J. Schoen		 source 6
SUGI 1983 Software for Statistical Graphics-An Overview Patricia M. Caporal,
C.J. Hahn		 source 10
SUGI 1983 Successful Statistical Consulting Douglas C. Montgomery source 4
SUGI 1983 Time Series Analysis of Highway Accident Data Ronald J. Classen,
David W. Elizandro,
Scott O. Starks		 source 3
SUGI 1983 Using and InterpretingARIMA, X11, FORECAST, andSTATESPACE John C. Brocklebank source 8
SUGI 1982 Basic Time Series Tools for Business Forecasting Mary Sue Dickerson,
Franklin S. Young		 source 6
SUGI 1982 Curriculum Approach to SAS Training Herbert J. Kirk source 3
SUGI 1982 Efficient Statistical Consulting in the Small University Environment David M. Smith source 3
SUGI 1982 Helpful Hints for Harmonious Data Analysis Philip Hanser source 2
SUGI 1982 New Time Series Features in SAS David M. DeLong source 3
SUGI 1982 Use of SAS to Analyze Experiments Conducted over Time with Multivariate Responses and Autocorrelated Errors Walter W. Stroup source 7
SUGI 1980 Analysis of a Fragmented Time Series Using GLM James E. Dunn source
SUGI 1980 Box-Jenkins Time Series Method and Computer Packages Syed Shahabuddin source 5
SUGI 1980 Fitting Time Series Using SAS David M. DeLong source 5
SUGI 1980 Recent Developments in BMDP of Special Interest to SAS Users James W. Frane source 8
SUGI 1978 The Data Base Approach at the Bureau of Labor Statistics Rudolph C. Mendelssohn source 4
SUGI 1977 SAS as Programming Tool and Central Data Interface with Other Statistical Software Douglas Cockrell,
Mike Foxworth,
Gary Griepentrog		 source
SUGI.ONE 1976 Econometric Uses of SAS Max Moszer,
Martha S. Shuler		 source 26
SUGI.ONE 1976 Using SAS for Univariate Time Series Analysis via the Box Jenkins Technique Mark J. Nicolich source 20

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