|Papers Topic List|
|March 2009||Experimenting Outside the Box: Using SAS/QC for Modern Applications of Experimental Design (PDF)
This paper demonstrates specialized features of SAS/QC software that enable you to apply the principles of experimental design beyond traditional applications.
|March 2008||How SASŪ9 Allows the Delivery of the Power of Predictive Analytics and Forecasting to the Masses (PDF)
The integrated analytics that SAS offers is the engine that provides the extra power that competitors cannot match in other market spaces such as data integration and business intelligence.
|March 2008||Retention Analytics for Human Capital Management (PDF)
Employee retention is an increasingly serious issue in many business sectors. Understanding which factors cause employees to leave and which actions retain them is an important Business Intelligence application. This paper demonstrates analytic methods to address this problem.
|March 2008||Small Improvements Causing Substantial Savings - Forecasting Intermittent
Demand Data Using SAS Forecast Server (PDF)
This paper exposes the inadequacy of continuous time series methods when compared to IDM for forecasting future average demand per period for intermittent time series. This paper demonstrates a technique and system of large-scale automatic forecasting of intermittent demand series. This paper explains how SAS Forecast Server is used as this system.
|March 2008||Two-Stage Variable Clustering for Large Data Sets (PDF)
In data mining, principal component analysis is a popular dimension reduction technique. It also provides a good remedy for the multicollinearity problem, but its interpretation of input space is not as good. To overcome the interpretation problem, principal components (cluster components) are obtained through variable clustering, which was implemented with PROC VARCLUS.
|March 2008||Using Copulas to Model Dependency Structures in Econometrics (PDF)
This paper introduces advanced copula modeling capabilities in the MODEL procedure. We also show how insight into the correlation structure of the copulas can be obtained by using animations produced by SAS.
|March 2008||Zero-Inflated Poisson and Zero-Inflated Negative Binomial Models Using the
COUNTREG Procedure (PDF)
This paper studies the performance of different count models on a simulated example. The results demonstrate that among the count models we consider, in many cases a Poisson model tends to be overly restrictive.