Large Sample Theory

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

1st draft of course notes for Large Sample Theory. This manuscript is unfinished. Revisions are ongoing. Not even close to being ready yet. The .PDF version below is as of Jan. 2023.

If you wish to contact the author, click here.

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

.PDF Version R Programs R Data R Code
lsampbk.pdf lspack.txt lsdata.txt lsrhw.txt
Table of Contents
Misc MDATA Files
Preface i-x   cont bodfat.lsp
Chapter 1-Introduction 1-48   ch1 boston2.lsp
Chapter 2-Univariate Limit Theorems 49-84   ch2 buxton.lsp, cbrain.lsp
Chapter 3-Multivariate Limit Theorems 85-96   ch3 credit.lsp, cyp.lsp
Chapter 4-Prediction Intervals and Prediction Regions 97--112   ch4 gladstone.lsp
Chapter 5-Confidence Regions and the Bootstrap 113-148   ch5 ICU.lsp
Chapter 6-Regression: GLMs, GAMs, and Statistical Learning 149-210   ch6 major.lsp
Chapter 7-Experimental Design and One Way MANOVA 211-211   ch7 marry.lsp, mbb1415
Chapter 8-Robust Statistics 213-284   ch8 museum.lsp, muss.lsp
Chapter 9-Time Series 285-285   ch9
Chapter 10-Graphical Diagnostics 287-300   ch10
Chapter 11-More Results 301-326   ch11
Bibliography- 327-332   bib
data- NA-NA   ch12 pollution.lsp
data- NA-NA   ch13 pov.lsp, povc.lsp
data- NA-NA   ch14
data- NA-NA   ch15 skeleton.lsp
data- NA-NA   ch16 wbb1415
data NA-NA   ch17  



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