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Linear Regression

Linear Regression

Paperback

ApplicationsProbability & Statistics

ISBN10: 3319856081
ISBN13: 9783319856087
Publisher: Springer
Published: Jul 25 2018
Pages: 494
Weight: 1.56
Height: 1.03 Width: 6.14 Depth: 9.21
Language: English

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.

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Olive, David J.

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Probability & Statistics