Prediction and Statistical Learning

Prediction and Statistical Learning by David Olive Preprint M-02-006 Copyright June 2016, Jan. 2022

2nd draft of course notes for Prediction and Statistical Learning. This manuscript is unfinished. Revisions are ongoing. Not even close to being ready yet. The .PDF version below is as of May 2023. If you wish to contact the author, click here. The complete text is in the file multnotes.pdf. The MDATA files are for ARC.
	.PDF Version	R Programs	R Data	R Code
	slearnnotes.pdf	slpack.txt	sldata.txt	slrhw.txt	hdrhw.txt

Table of Contents	Pages	PDF	Misc MDATA Files
Preface	i-x	cont	bodfat.lsp
Chapter 1-Introduction	1-74	ch1	boston2.lsp
Chapter 2-Prediction Regions and the Bootstrap	75-142	ch2	buxton.lsp, cbrain.lsp
Chapter 3-Multiple Linear Regression	143-208	ch3	credit.lsp, cyp.lsp
Chapter 4-Additive Error Regression, GLMs, and GAMs	209-296	ch4	gladstone.lsp
Chapter 5-Discriminant Analysis	297-340	ch5	ICU.lsp
Chapter 6-Multivariate Analysis	341-348	ch6	major.lsp
Chapter 7-Cluster Analysis	349-356	ch7	marry.lsp, mbb1415
Chapter 8-MLR with Heterogeneity	357-366	ch8	museum.lsp
Chapter 9-High Dimensional Statistics	357-366	ch9	muss.lsp
Chapter 10-Multivariate Linear Regression	357-366	ch10
Chapter 11-Stuff for Students	357-366	ch11	pollution.lsp
Bibliography-	367-392	bib
data-	NA-NA	ch	povc.lsp
data-	NA-NA	ch	pov.lsp
data-	NA-NA	ch
data-	NA-NA	ch	skeleton.lsp
data-	NA-NA	ch
data-	NA-NA	ch	wbb1415
data	NA-NA	ch

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