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96 papers and 3 presentations; 93 titles.

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Conference × Year × Title × Authors Extras Pages
SESUG 2024 Advanced DATA Step Look-Back and Look-Ahead Techniques Joshua M. Horstman source 5
WUSS 2024 Advanced DATA Step Look-Back and Look-Ahead Techniques Joshua M. Horstman source 5
SESUG 2023 Forecasting Goals for Student Success Metrics in Accountability Performance Reporting using SAS Visual Analytics Xiaoying Liu,
Hennadii Balashov		 source 9
SESUG 2023 Two illustrations of the Quantity Theory of Money: A Restatement Lawrence Ogbeifun source 81
SGF 2020 Scalable Cloud-Based Time Series Analysis and Forecasting Using Open Source Software Javier Delgado source 21
SESUG 2019 The Best of Both Worlds: Forecasting Using Time Series with Inputs David A. Dickey source 19
SGF 2019 IFRS9: Using SAS/ETD Software and SAS Studio to Select Macro Economic Variables Julio Alberto Campa Vega Filho source 19
SGF 2019 The Best of Both Worlds: Forecasting Using Time Series with Inputs David A. Dickey source 19
SESUG 2018 Forecasting: Something Old, Something New David A. Dickey source 26
WUSS 2018 Forecasting: Something Old, Something New David A. Dickey source 26
SGF 2018 Forecasting: Something Old, Something New David A. Dickey source 26
SGF 2017 Creating Daily Rolling 6-Month Average and Cumulative Enrollment Graphs Using PROC EXPAND and INTNX Susan Schleede source 10
SGF 2017 Know Your Tools Before You Use Justin Jia source 16
SGF 2017 Production Forecasting in the Age of Big Data in the Oil and Gas Industry [presentation] Vipin Prakash Gupta,
Satyajit Dwivedi		 source 17
SCSUG 2016 Effective method on curing heart disease K. Varadarajan,
Surya Bhaskar Ayyalasomayajula		 source 12
SESUG 2016 Using PROC EXPAND to Easily Manipulate Longitudinal and Panel Data Matthew J. Hoolsema,
Carnegie Mellon		 source 6
SGF 2016 Stored Processes and SAS Visual Analytics: Giving Users the Power to Load Renato Luppi,
Varsha Chawla		 source 21
SGF 2016 Upgrade from ARIMA to ARIMAX to Improve Forecasting Accuracy of Nonlinear Time-Series: Create Your Own Exogenous Variables Using Wavelet Analysis Woranat Wongdhamma source 16
SGF 2016 What's the Difference? David A. Dickey source 17
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
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
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 Innovative Techniques: Doing More with Loops and Arrays Arthur L. Carpenter 14
MWSUG 2012 Setting the Table ... of Contents: Using SAS ODS PDF Features to Organize, Link, and Navigate a Report Betsy Enstrom 4
WUSS 2012 Innovative Techniques: Doing More with Loops and Arrays Arthur L. Carpenter source 14
PharmaSUG 2012 Innovative Techniques: Doing More with Loops and Arrays Arthur L. Carpenter source 13
SGF 2012 A Week in the Life: A Visual Analysis of Internet Use by School-Age Students Simon J. King,
Aaron Daniels,
Jacob Warwick		 source 12
SGF 2012 Comparing Stock Returns Forecasting Methods Using SAS Wei Wang,
Arthur X. Li		 source 8
SGF 2012 Weighted Portmanteau Tests Revisited: Detecting Heteroscedasticity, Fitting Nonlinear and Multivariate Time Series Thomas J. Fisher source 12
MWSUG 2011 Does Lawrence Smoking Ban Impact Kansas Liquor Sales? Lijia Mo 12
NESUG 2011 Baseball with Popcorn, Statistics and SAS - What A Mix David W. Franklin 8
SGF 2011 Extending SAS High-Performance Forecasting Using User-Defined Models and External Forecasts Udo Sglavo source 9
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 2010 Building Latent Growth Models Using PROC CALIS: A Structural Equation Modeling Approach Teck Kiang Tan,
Trivina Kang,
David Hogan		 source 19
SGF 2010 Stupid Human Tricks with PROC EXPAND David L. Cassell source 6
MWSUG 2009 Time Series Analysis 101: an introduction using Base SAS and SAS STAT David J. Corliss 7
SGF 2009 Structural Analysis of Time Series Using the SAS/ETS UCM Procedure Rajesh S. Selukar source 13
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
NESUG 2007 PROC EXPAND to the Rescue! Premal Vora 5
SGF 2007 Data Mining to Investigate the Prescribing of Medications Longitudinally Mussie A. Tesfamicael source 17
SGF 2007 Methodology for Railway Demand Forecasting Using Data Mining Giovanni M. Viglioni source 11
SGF 2007 OLS Regression? Auto-Regression? Dynamic Regression? Rodger Zhang source 12
SESUG 2006 Detection and Quantification of Asymmetric Peaks Carry W. Croghan,
Ronald W. Williams		 source 13
SUGI 2006 Modeling Water Quality Trend in Long Term Time Series Anpalaki J. Ragavan,
George C. J. Fernandez		 source 10
SUGI 2005 Comparing the SAS Forecasting System with PROC HPF and SAS Enterprise Miner Patricia B. Cerrito source 9
SUGI 2005 Stationarity Issues in Time Series Models David A. Dickey source 17
SESUG 2004 Case Studies in Time Series David A. Dickey source 10
WUSS 2003 Using the ARIMA Modeling Capabilities of SAS to Forecast Rates of Febrile Respiratory Infection at Eight U.S. Military Recruit Training Centers Christian J. Hansen,
Anthony W. Hawksworth,
Phillip I. Good,
Margaret A. K. Ryan		 source 3
SUGI 2003 Case Studies in Time Series David A. Dickey source 9
WUSS 2001 Detecting Seasonality in Univariate Time Series Data Using the SAS System Joseph E. Earley,
Seid M. Zekavat		 source 6
WUSS 2000 SAS STAT applications in Econometrics Mathura Thillainathan,
George C. J. Fernandez		 source 10
SEUGI 2000 Development of Micro-Aggregation System for Confidential Data [presentation] L. Bechet,
P. Loosveldt,
T. Le Tri		 source 44
SCSUG 1999 Using JMP for Technical Analysis of Stocks in Highly Volatile Markets William R. Gjertsen 7
SESUG 1999 Using JMP for Technical Analysis of Stocks in Highly Volatile Markets William R. Gjertsen source 7
WUSS 1999 Investigating Seasonality in BLS Data Using PROC ARIMA Joseph E. Earley source 6
WUSS 1999 Using JMP for Technical Analysis of Stocks in highly voloatile markets William Gjersen source 7
SEUGI 1999 Quast: the Monsanto system for quality control and analysis [presentation] Stijn Vermeulen source 22
SUGI 1999 Autoregressive Integrated Moving Average Models for Comparing Forecasted to Actual Values of CPU Workloads for Open Systems Anthony C. Waclawski source 10
SESUG 1998 Regression with Time Series Errors David A. Dickey 9
SCSUG 1997 The Use of PROC ARIMA to Test An Intervention Effect Neil S. Fleming,
Eric Gibson,
David G. Fleming		 8
WUSS 1997 Analysis of Time Series Data - An Application in Health Care Sujaya Parthasarathy source 6
NESUG 1997 Time Series Magic: Smoothing, Interpolating, Expanding and Collapsing Time Series Data With PROC EXPAND Andrew H. Karp 5
SEUGI 1997 Comparison between different methods to estimate orders in ARIMA models Dominique LADIRAY,
Michel Grun-Rehomme		 source 11
SEUGI 1996 ARIMA-model application for forecasting futures markets A. E. Smirnov,
S. V. Kutsev,
V. E. Sorokoumov		 source 4
SUGI 1996 Using PROC ARIMA to Test an Intervention Effect Neil S. Fleming,
Eric Gibson,
David G. Fleming		 source 10
SCSUG 1995 The Use of PROC ARIMA to Test An Intervention Effect Neil S. Fleming 4
NESUG 1995 A SAS Macro Introduction to Statistical Quality Control of Longitudinal Data Timothy D. Kelly 2
WUSS 1995 An Introduction to PROC ARIMA Using Macroeconomic Time Series Joseph E. Earley source 14
SCSUG 1994 Intervention Analysis in Vocational Rehabilitation David B. Cohen 12
SUGI 1993 Forecasting Methods Mark Little source 13
SCSUG 1992 The Use of PROC ARIMA to Perform Time-Series Intervention Analysis of the Impact of the Texas 1989 Motorcycle Helmet Law on Total and Head-Related Fatalities Neil S. Fleming 21
SEUGI 1992 Comparing Splines and Kriging Using SAS/GRAPH Software as an Agronomical Application A. Castrignano,
F. Caspalino,
L. Romito,
V. Zupa		 source 11
SEUGI 1992 Using SAS Macros and PROC IML to Create Special Designs for Use in Generalised Linear Models John Hendrickx source 22
SUGI 1992 A Supplemental SAS Function for Computing Moving Average Shi-Tao Yeh source 3
SUGI 1992 Using the ARIMA Procedure in Forecasting the Demand and Utilization of Inpatient Hospital Services John J. Hisnanick source 9
SEUGI 1991 Rhythm Pattern Analysis - A Simplified Approach Neil Atkins source 7
SUGI 1991 Uses of SAS Software for Implementation of SPC on Continuous Processes Robert V. Baxley Jr. source 7
SUGI 1990 Determining Weight Values for EWMA Control Schemes Using the ARIMA Procedure John C. Brocklebank source 10
SUGI 1989 Estimating the Minimum Total Error-Squares Weight Parameter for the Geometric Moving Average Melvin T. Alexander,
Christine Macklin		 source 6
SEUGI 1987 A Macro for Weighted Moving Averages Leena Metso source 4
SEUGI 1987 Economically Active Population Estimates and Projections, 1950-2025 B. Binesh Aghevli,
C. Gerlier		 source 16
SUGI 1987 Seasonal Adjustment Operations of Canadian Socio-Economic Time Series Estela Bee Dagum,
Misako Grafton		 source 5
SUGI 1986 Performing the X1 1ARIMA Seasonal Adjustment John C. Brocklebank,
David A. Dickey		 source 10
SUGI 1985 Changes and Enhancements to SAS/ETSSoftware David M. DeLong,
Leigh A. Ihnen,
Mark Little		 source 12
SUGI 1985 PROVAL-An Automated Method for Evaluating Trade and Consumer Promotions for Package Goods Industries Ambar G. Rao,
Ross Dennis,
Douglas Grady		 source 5
SEUGI 1984 New Statistical Features in SAS Gerhard Held source 13
SEUGI 1984 Using SAS for Interactive Logistical Support Lionel P. Lecoq source 14
SUGI 1984 Changes and Enhancements to SAS/ETS Procedures David M. DeLong,
Leigh A. Ihnen,
Mark Little		 source 6
SUGI 1983 An Algorithm for Producing Exact Maximum Likelihood Estimates for an ARIMA(p,q) Process Carol M. Reilly source 3
SUGI 1983 Offense, Defense, and Causality in Baseball Charles F. Hofacker source 5
SUGI 1982 New Time Series Features in SAS David M. DeLong source 3
SUGI 1981 A Comparison of Several Approaches for Calculating LC50s for Binary Responses from Toxicological Experiments Charles M. Bundrick,
Jerry L. Oglesby		 source 8
SUGI 1980 Box-Jenkins Time Series Method and Computer Packages Syed Shahabuddin source 5
SUGI 1977 Creating a Running Mean of the Last K-Observations Lagged L-Observations Glenn A. Augustine,
Terry M. Therneau		 source 2
SUGI.ONE 1976 Using SAS for Univariate Time Series Analysis via the Box Jenkins Technique Mark J. Nicolich source 20

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