Michael Panik

Regression Modeling

Methods, Theory, and Computation with SAS

• Broschiertes Buch

Produktbeschreibung

Requiring only basic knowledge of statistics and calculus, this comprehensive, accessible text provides an introduction to a diverse assortment of regression techniques using SAS to solve a wide variety of regression problems. The author fully documents the SAS programs and thoroughly explains the output produced by the programs. He explores the well-known methods of OLS and maximum likelihood regression before developing many alternative regression techniques, such as nonparametric, logistic, Bayesian, robust, fuzzy, random coefficients, spatial, polynomial, ridge, semiparametric, and more. The book also covers nonlinear and time series modeling.

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Produktdetails

• Verlag: Chapman and Hall/CRC
• Seitenzahl: 832
• Erscheinungstermin: 7. Oktober 2019
• Englisch
• Abmessung: 254mm x 178mm x 44mm
• Gewicht: 1533g
• ISBN-13: 9780367385675
• ISBN-10: 0367385678
• Artikelnr.: 58052720

Autorenporträt

Panik, Michael

Inhaltsangabe

Preface. Review of Fundamentals of Statistics. Bivariate Linear Regression
and Correlation. Misspecified Disturbance Terms. Nonparametric Regression.
Logistic Regression. Bayesian Regression. Robust Regression. Fuzzy
Regression. Random Coefficients Regression. L1 and q-Quantile Regression.
Regression in a Spatial Domain. Multiple Regression. Normal Correlation
Models. Ridge Regression. Indicator Variables. Polynomial Model Estimation.
Semiparametric Regression. Nonlinear Regression. Issues in Time Series
Modeling and Estimation. Appendix. References. Index.