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CRC Press Regression Modeling: Methods, Theory, Computation SAS

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Description

Regression Modeling: Methods, Theory, and Computation with SAS provides a comprehensive introduction to diverse regression techniques using SAS software for solving complex regression problems. The book fully documents SAS programs and thoroughly explains their output, starting with ordinary least squares (OLS) methodology before progressing to alternative approaches. Readers gain practical knowledge in nonparametric regression, logistic regression including Poisson variants, Bayesian regression methods, robust regression techniques, fuzzy regression applications, and random coefficients regression. Each method is presented with both theoretical foundations and computational implementation, making this resource ideal for statisticians, economists, and data analysts seeking to master regression analysis in SAS. The detailed explanations and documented code examples enable practitioners to apply these advanced techniques to real-world data problems across econometrics and applied statistics.

Key Features

Covers ordinary least squares (OLS) regression as the foundational approach before introducing alternative methods.

Includes logistic regression and Poisson regression techniques for binary and count data analysis.

Explores nonparametric regression methods that do not assume specific functional forms.

Presents Bayesian regression approaches for incorporating prior information into models.

Demonstrates robust regression techniques designed to handle outliers and data anomalies.

Details fuzzy regression applications for problems with imprecise or uncertain data.

Provides fully documented SAS programs with thorough explanations of program output.

Covers random coefficients regression for modelling heterogeneity across observations.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
30 April 2009
Listed Since
06 June 2008

Barcode

No barcode data available

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