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Linear Regression

Language EnglishEnglish
Book Paperback
Book Linear Regression David J. Olive
Libristo code: 20094123
Publishers Springer International Publishing AG, July 2018
This text covers both multiple linear regression and some experimental design models. The text uses... Full description
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This text covers both multiple linear regression and some experimental design models. The text uses the response plot to visualize the model and to detect outliers, does not assume that the error distribution has a known parametric distribution, develops prediction intervals that work when the error distribution is unknown, suggests bootstrap hypothesis tests that may be useful for inference after variable selection, and develops prediction regions and large sample theory for the multivariate linear regression model that has m response variables. A relationship between multivariate prediction regions and confidence regions provides a simple way to bootstrap confidence regions. These confidence regions often provide a practical method for testing hypotheses. There is also a chapter on generalized linear models and generalized additive models. There are many R functions to produce response and residual plots, to simulate prediction intervals and hypothesis tests, to detect outliers, and to choose response transformations for multiple linear regression or experimental design models. This text is for graduates and undergraduates with a strong mathematical background. The prerequisites for this text are linear algebra and a calculus based course in statistics.

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About the book

Full name Linear Regression
Language English
Binding Book - Paperback
Date of issue 2018
Number of pages 494
EAN 9783319856087
Libristo code 20094123
Weight 7606
Dimensions 155 x 235 x 28
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