PDF-Bootstrapping Regression Models Appendix to An R and SPLUS Companion to Applied Regression PDF document

The term bootstrapping due to Efron 1979 is an allusion to the expression pulling oneself up by ones bootstraps in this case using the sample data as a population

Upload by marina-yarberry
Published on 2015-02-25

Presentation Embed Code

<iframe width="560" height="315" src="https://www.docslides.com/embed/39452" frameborder="0" allowfullscreen></iframe>

Download Presentation

Download Presentation The PPT/PDF document "Bootstrapping Regression Models Appendix..." is the property of its rightful owner. Permission is granted to download and print the materials on this web site for personal, non-commercial use only, and to display it on your personal computer provided you do not modify the materials and that you retain all copyright notices contained in the materials. By downloading content from our website, you accept the terms of this agreement.

Bootstrapping Regression Models Appendix to An R and SPLUS Companion to Applied Regression: Transcript

PDF-Bootstrapping Regression Models Appendix to An R and SPLUS Companion to Applied Regression PDF document

Presentation Embed Code

Download Presentation

Bootstrapping Regression Models Appendix to An R and SPLUS Companion to Applied Regression: Transcript

Related Contents

Nonparametric Regression Appendix to An R and SPLUS Companion to Applied Regression JohnFox

Nonlinear Regression and Nonlinear Least Squares Appendix to An R and SPLUS Companion

Robust Regression Appendix to An R and SPLUS Companion to Applied Regression JohnFox January

Cox ProportionalHazards Regression for Survival Data Appendix to An R and SPLUS Companion

Linear Mixed Models Appendix to An R and SPLUS Companion to Applied Regression JohnFox

Frames Environments and Scope in R and SPLUS Appendix to An R and SPLUS Companion to Applied

Applying bootstrap methods to time series and regression mo

Statistical Inference and Regression Analysis:

Lecture 0

Regression and Forecasting Models

AMS 572 Group #2 Multiple Linear Regression

What is the future of p-values?

Current Statistical Issues in Dissolution Profile Compariso

Statistical Inference