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Technical Reviewers Book List


Time Series Analysis in SAS: Beyond Forecasting
By David J. Corliss

Written for the intermediate and advanced SAS user, this book has as its focus the many practical applications and concrete examples in SAS of a wide variety of important time series analysis tools other than forecasting. Many of these tools can be found in statistical journals, but these publications lack application to the situations faced by researchers in many areas. Moreover, a complete handbook for time series applications exists only for ARIMA models in general and forecasting in particular, not the many other techniques described in academic journals. This book will complement SAS's successful text, SAS for Forecasting Time Series, by John C. Brocklebank and David A. Dickey, expanding the SAS tools available to users to include many more, such as the following: cluster analysis, data visualization, work with missing data, and wavelets. This book also introduces time series analysis in SAS to researchers now using R for time series analysis.

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SAS Metadata Dictionary Tables and SASHELP Views: Learning Metadata by Example
By Kirk Paul Lafler

SAS users can quickly and conveniently obtain useful information about their SAS session with read-only SAS data views called Dictionary tables or SASHELP views. At any time during a SAS session, information about currently defined system options, libnames, table names, column names, and attributes, formats, indexes, and more can be accessed and captured. This book will help all levels of SAS users learn all about the world of metadata in SAS software: With an instructive and conversational voice, SAS consultant and author Kirk Paul Lafler explains the purpose of each Dictionary table and SASHELP view, its contents, and many uses. A comprehensive and real-world, step-by-step, approach is presented, illustrating popular DATA step, PROC, and Enterprise Guide programming examples. This book explores the purpose of Dictionary tables and views, how they are accessed, and what information is available to SAS users. Readers learn how these important tables and views can be accessed and applied, using real-world scenarios.

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An Introduction to Financial Analytics Using SAS
By Sourish Das, Lokesh Nagar, and Bala Gopalakrishnan

This example-driven book provides an easy-to-understand approach to learning finance and statistical modeling, with special attention to application with the use of SAS. Most books on financial engineering are quite mathematical, requiring an advanced background in stochastic calculus. In this book the authors have taken a data mining approach, which blends theory and practice. They present an easy introduction to the topics of finance and statistical modeling, with sufficient methodological detail and the required SAS code to implement models in practice with real data. The book is especially suitable for undergraduate to masters-level students of statistical finance. Professionals in finance will also find it handy for model implementation and indicators using SAS.

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SAS Optimization Essentials: A Step-by-Step Guide for New Users of PROC OPTMODEL
By T. Glenn Bailey

T. Glenn Bailey’s SAS Optimization Essentials: A Step-by-Step Guide for New Users of PROC OPTMODEL shows you how easy it is to employ optimization using PROC OPTMODEL, while simultaneously leveraging the overall SAS environment. With this book you will quickly bridge the gap between optimization formulation and solution implementation, by effectively translating mathematical models into SAS using PROC OPTMODEL. Part 1 introduces essential PROC OPTMODEL programming, declaration, and procedural syntax; data I/O; and extensive examples of linear programming and mixed-integer programming problems. Part 2 provides advanced examples of the topics covered in part 1, and reviews how PROC OPTMODEL can be used with SAS/GRAPH and the Macro Programming Language.

SAS Optimization Essentials is unique in that it focuses on the essential statements and syntax necessary to run a majority of optimization problems, and arranges the presentation of PROC OPTMODEL’s procedures and syntax to follow the process of mathematically formulating an optimization problem. Loaded with examples, the book teaches the reader how to "think in PROC OPTMODEL" the same way they already "think in mathematical terminology" when considering an optimization problem. If you are a SAS user and want to use SAS for optimization, this is the book for you.


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