SEUGI 1985 Papers - Index

37 papers. Source: SEUGI (SAS European Users Group International) conference proceedings.

#	Title ×	Authors ×	Abstract ×	Keywords ×	Extras	Pages
1	A DB2 Interface to the SAS System under MVS	Herbert Sinwel		proc step, dataset, proc print, proc sql, select	source	5
2	A Help for End-Users SAS Software for Analysis of Surveys	Gerard Hatabian		univariate analysis, proc freq, proc princomp	source	10
3	A Month in the Life of a 3083-JX CPU	Julian Ashworth		trend analysis, capacity planning	source	15
4	A User-Friendly Application System Based on the SAS System	Franz Lasinger		regression analysis, data science	source	8
5	Advanced SYSTEM 2000 DBMS Techniques	Ron Hults			source	28
6	An Interface Between the SYSTEM 2000 DBMS and the SAS System	Jim Becker		where statement, sas output	source	6
7	Analysing the Performance of VMS with the SAS System	Alan Scott	This paper describes techniques for accessing data available from VMS for use. in monitoring the performance of a VAX/VMS system. The details of actual performance monitoring theory' and techniques are not covered in this paper. The techniques" available in SAS for accessing external files containing performance data generated by, VMS and its utilities is covered. '. The data available comes from several sources . The VMS accounting dat, file provides a source of information about individual process resource usage. The VMS VERIFY command can be used to generate a binary data file containing infol'mation about disk usage. Perhaps the most interesting source of data .is the output of tnl!' MONITOR utilitY. Because thisissystem';'wide information already collected in a cUinulative tiM'ewith regular samples, it lends itself easily to analysis of 'system usage arid efficiency	sample, length statement, dataset	source	6
8	Changes and Enhancements to the TABULATE Procedure	Bernie Ruane	There are several enhancements to `PROC TABULATE` available, in the next major release of the SAS !iystem. This tutorial begins with a review of the fundamental langua;'" features of TABULATE. The rest of the tutorial describes en han-cements including correct interleaving of crossed subgroups applicatIon of user-defined formats in table cells a CO"'DENSE option to -put multiple 'logical pages on a single physical page a BOX option to put page dimension text, a vanable label, or a character string in the empty box over the ,row titles using analysis variables in denominator definitions. -- The new algorithm for interleaving crossed subgroups is mo'st useful-for locating subtotals of classif,cation groups immediately following the levels of each group	class variable, proc step, response variable, proc tabulate, user-defined format	source	15
9	Copying SAS PROC Definitions Using the SAS ISPF Model Command	Rolf Steenge		proc step, dataset	source	5
10	Cost Analysis with the SAS System The Other Side of Capacity Management	Carlo Grandi		capacity planning, bar chart	source	8
11	Creating Sample Program Brochures Using DCF	Rolf Steenge		sample, anova, proc step, sas log, dataset, proc cancorr, proc format, sas output, correlation, proc print	source	9
12	Data Analysis and the Information Centre	Aale Roos		data science, data wrangling	source	5
13	Data Set Manipulation by Query Language	David Burrage		error message, macro definition	source	5
14	Differential Interface to the SAS System with Variable Selection Lists	Peter Arklint		proc step, proc print, proc tabulate, in= option, variable list, group by	source	12
15	Early Experiences with SAS/AF Software	Erik W. Tilanus		proc step, audit trail, run, macro variable, macro definition, error message, call symput, %if-%then-%else	source	10
16	Enhancements to SAS/FSP Software - including the FSCALC Procedure	Hans Munch, Philip J. Winters	This paper discusses the changes and enhancements to the `SAS/FSP` software. Some changes are common to all `SAS/FSP` procedures, while others affect only a single procedure or a particular screen within a procedure. All the screens you create with the FSCAlC and FSEDIT procedures, letters and forms created with `PROC FSLETTER`, and function key definition screens are stored in catalogs. Catalogs are not SAS data sets, which can be accessed in the same manner as data sets are cu rrently accessed. Catalog management involves understanding how the catalogs are set up and manipulated. A common text editor is now available for FSCAlC program screens, `PROC FSEDIT` screen modification, and FSlETTER forms and letters. In addition, `PROC FSEDIT` has changed significantly in order to protect screens and to regularly store data entered' without having to exit the procedure	proc step, catalog entry	source	5
17	Enhancements to the GREPLAY Procedure	Steve Morton		proc step, proc greplay, proc gplot	source	5
18	Evolution of Data Management	Johan de Wit		data dictionary	source	31
19	First Impressions of the SAS System - Version 5	Phil Davies		proc step, proc iml	source	10
20	General Enhancements to the SAS/GRAPH Software	Alan Russell			source	5
21	Micro as an Effective Tool in Using SAS Software	Hannu Ritvanen			source	6
22	MXG Version 2	Jim Thomason		output, sas output	source	2
23	New Features of the SAS/ETS and SAS/OR Software in Version 5	John C. Brocklebank		proc step, proc autoreg, missing value, dataset, regression analysis, autoregressive model, residual, integer programming, maximum likelihood estimation, likelihood function, predictor variable, proc calis, time series analysis, monte carlo, proc model, confidence interval, proc forecast, covariance, proc arima	source	37
24	Phacit - A Marketing Information System for the Pharmaceutical Industry	Peter Beutel		dataset, final analysis	source	12
25	Regression Analysis and other SAS Procedures for Assessing Credit Risk	Raxa Vaid	The volume of accounts which are one month late with a repayment is often very large, sometimes up to 30% of a portfolio. It is useful to be able to assess the risk involved in these accounts. Up to 50% of them repay in full in the following month and so are not considered to be risky. About 25% remain one month outstanding and only 25% do not pay all overdue amounts. Effort can be directed towards chasing accounts least likely to pay if these can be Identified-, and time and goodwill saved by ignoring those who do.repay in full. To make one month ahead forecasts of overdue accounts, data containing past behaviour of· individual accounts is extracted. MEANS, FREQUENCY and CORRELATIONS procedures are used for preliminary analysis·. The more significant ·variables are then run through regression analysis. The final score can be validated using the Chi-square statistic and the model tested for quality using the Kolmogorov-Smirnov test	regression analysis, sample, dataset, proc step, credit risk, proc freq, data cleaning	source	10
26	Run Time Component Analysis Using MICS	A. R. MacDonald	One of the fundamental techniques employed in computer performance evaluation (CPE) studies is the reduction of process execution'time into its component parts. In this paper, we wi 11 examine how MVS/XA SMF andRMF data can be used to analyse the execution time of batch jobs. . 1.0 Introduction One of the most common problems presented to the performance analyst is a process execution time that does not meet the expectation (i.e., service objective) of a user. When presented with such a problem, the most logical approach is to reduce the execution time into its component parts. Once· this process has been completed, the analyst can identify specific' serv.ice times or server delays that can be improved to achieve the desired service level. Prior to MVS/XA, SMF and RMF data did not prov ide sufficient information to effectively reduce the execution time of batch programs	cpu time, format statement	source	9
27	SAS Institute's Best Active Data Dictionary	Gil D. Tolan		data dictionary	source	3
28	SAS/IML Software - An Interactive Matrix Language for Version 5	Mogens Weinreich			source	3
29	Statistical Enahancements to the SAS System	Gerhard Held	The purpose of this paper is to introduce the n~ procedures and enhancements in the statistical domain of the base SA~ System, Version 5. We will concentrate on the major items, discuss applications and syntax, and will give examples if feasible. The statistical enhancements can be classified into four major types of analysis: categorical data analysis, analysis of repeated measurement models, new· procedures for analysis ot survival data, and enhancements in cluster analysis. 1. Categoricai Data Analysis The capabilities of SAS software for categorical data analysis have increased dramatically over the past few years. The primary procedures for categorical data analysis in Version 5 of the SAS System are	alternative hypothesis, relative risk, correlation, proc freq, confidence interval, sample	source	20
30	Test Procedures for Model Selection and Model Validation	Wil Velding		regression analysis, null hypothesis, sas output, model validation, instrumental variables, proc step, degrees of freedom, f distribution, feature selection, data cleaning, dataset, significance level, response variable, predictor variable, proc autoreg, proc reg, binary variable, macro definition	source	23
31	The Annotate Facility in SASGRAPH Software	Philip J. Winters	The annotate facility permits you to customize `SAS/GRAPH` procedure output. The facility is capable of defining polygons, controlling pen movement, placing text on a page, etc. The facility takes graphics commands from special SAS data sets	dataset, proc step	source	5
32	The Best Mode of Use for the Cubic Clustering Criterion	Jean-Luc Molliere		proc step, proc fastclus, proc cluster, monte carlo, proc princomp	source	23
33	The Display Manager System	Daniel Delorge		proc step, sas log	source	10
34	The Nonparametric Tests in SURVTEST, COXREGR and PHGLM	Jan Mulder		sample, censoring, proc phreg, log-rank test, likelihood function, wilcoxon test	source	7
35	The Use of Annotate under VMS to Produce Customised Graphs	Ian Sedgwick		proc gplot, proc step	source	22
36	Using SAS/GRAPH Software to Analyse IDMS	Peter Bailey		proc freq, audit trail	source	13
37	Using the SAS System for Course Authoring	Gerhard Held		proc step, dataset	source	6

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