Wicklin R. Simulating Data with SAS

SAS Institute Inc., 2013. — 362 p. — ISBN: 1612903320, 9781612903323Data simulation is a fundamental technique in statistical programming and research. Rick Wicklin's Simulating Data with SAS brings together the most useful algorithms and the best programming techniques for efficient data simulation in an accessible how-to book for practicing statisticians and statistical programmers.
This book discusses in detail how to simulate data from common univariate and multivariate distributions, and how to use simulation to evaluate statistical techniques. It also covers simulating correlated data, data for regression models, spatial data, and data with given moments. It provides tips and techniques for beginning programmers, and offers libraries of functions for advanced practitioners.
As the first book devoted to simulating data across a range of statistical applications, Simulating Data with SAS is an essential tool for programmers, analysts, researchers, and students who use SAS software.Essentials of Simulating Data
Introduction to Simulation
Simulating Data from Common Univariate Distributions
Preliminary and Background Information
Basic Simulation Techniques
Simulating Data to Estimate Sampling Distributions
Using Simulation to Evaluate Statistical Techniques
Strategies for Efficient and Effective Simulation
Advanced Simulation Techniques
Advanced Simulation of Univariate Data
Simulating Data from Basic Multivariate Distributions
Advanced Simulation of Multivariate Data
Building Correlation and Covariance Matrices
Applications of Simulation in Statistical Modeling
Simulating Data for Basic Regression Models
Simulating Data for Advanced Regression Models
Simulating Data from Times Series Models
Simulating Data from Spatial Models
Resampling and Bootstrap Methods
Moment Matching and the Moment-Ratio DiagramAppendix A. A SAS/IML Primer