Simulating Data with SAS

Wicklin, Rick

ISBN 10: 1612903320 / ISBN 13: 9781612903323

Editore: SAS Institute, 2013

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Fast & Free Shipping â Very good condition with a clean, sturdy cover and crisp pages. Gently used with only minor shelf wear. May include a few subtle marks, but overall a well-maintained copy ready to enjoy.Supplemental items like CDs or access codes may not be included.

Codice articolo ZWV.1612903320.VG

Dati bibliografici

• Titolo: Simulating Data with SAS
• Editore: SAS Institute
• Data di pubblicazione: 2013
• Lingua: Inglese
• ISBN 10: 1612903320
• ISBN 13: 9781612903323
• Rilegatura: Brossura
• Condizione: very_good

Descrizione articolo

Riassunto

Data 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.

Informazioni sull?autore

Rick Wicklin is a principal researcher in computational statistics at SAS, where he develops and supports the IML procedure and the SAS/IML Studio application. He received a PhD from Cornell University and has been a SAS user since 1997. Rick has presented numerous tutorials and papers at statistical and SAS users group conferences and is active in the American Statistical Association. Rick maintains a blog for statistical programmers at blogs.sas.com/content/iml/.