Theory for Linear Models

by David Olive
        Preprint M-02-006
        Copyright July 2018, Jan. 2022

1st draft of course notes for Theory for Linear Models. This manuscript is unfinished. Revisions are ongoing. The .PDF version below is as of Jan. 2022.

If you wish to contact the author, click here.

The complete text is in the file linmodnotes.pdf. The MDATA files are for ARC.

.PDF Version R Programs R Data R Code
linmodnotes.pdf linmodpack.txt linmoddata.txt linmodrhw.txt
Table of Contents
Misc MDATA Files
Preface i-xii   cont bodfat.lsp
Chapter 1-Introduction 1-69   ch1 boston2.lsp
Chapter 2-Full Rank Linear Models 71-112   ch2 buxton.lsp, cbrain.lsp
Chapter 3-Nonfull Rank Linear Models and Cell Means Model 113-132   ch3 credit.lsp, cyp.lsp
Chapter 4-Prediction and Variable Selection When n >> p 131-202   ch4 gladstone.lsp, hbk.lsp
Chapter 5-Statistical Learning Alternatives to OLS 203-264   ch5 ICU.lsp
Chapter 6-What If n is not >> p? 265-269   ch6 major.lsp
Chapter 7-Robust Regression 271-351   ch7 marry.lsp, mbb1415
Chapter 8-Multivariate Linear Regression 353-398   ch8 museum.lsp, muss.lsp, nasty.lsp
Chapter 9-One Way MANOVA Type Models 399-416   ch9 pollution.lsp
Chapter 10-1D Regression 417-495   ch10 pov.lsp, povc.lsp
Chapter 11-Stuff for Students 497-512   ch11 skeleton.lsp, wood.lsp
Bibliography 513-541   bib



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