Statistical Programming with SAS/IML Software

Author:   Rick Wicklin
Publisher:   SAS Publishing
ISBN:  

9781607646631


Pages:   460
Publication Date:   22 October 2010
Format:   Paperback
Availability:   Out of print, replaced by POD   Availability explained
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Statistical Programming with SAS/IML Software


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Overview

SAS/IML software can be a powerful tool for data analysts, as it allows implementation of statistical algorithms that are not available in any SAS procedure. Rick Wicklin's Statistical Programming with SAS/IML Software is the first book to provide a comprehensive description of the software and how to use it. He presents tips and techniques that enable you to use the IML procedure and the SAS/IML Studio application efficiently. In addition to providing a comprehensive introduction to the software, the book also shows how to create and modify statistical graphs; call SAS procedures and R functions from an IML program; and implement such modern statistical techniques as simulations and bootstrapping methods in the SAS/IML language. Written for data analysts working in all industries, graduate students, and consultants, the book includes numerous code snippets and more than 100 graphs.

Full Product Details

Author:   Rick Wicklin
Publisher:   SAS Publishing
Imprint:   SAS Publishing
Dimensions:   Width: 21.00cm , Height: 2.30cm , Length: 28.00cm
Weight:   1.027kg
ISBN:  

9781607646631


ISBN 10:   1607646633
Pages:   460
Publication Date:   22 October 2010
Audience:   General/trade ,  General
Format:   Paperback
Publisher's Status:   Active
Availability:   Out of print, replaced by POD   Availability explained
We will order this item for you from a manufatured on demand supplier.

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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/.

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