Abstract

http://ssrn.com/abstract=1012661
 
 

References (40)



 


 



Thinking the Unthinkable: Modern Non-Parametric Re-sampling Methods


Giampiero Favato


Kingston University

Roger Mills


Henley Management College - Henley Centre for Value Improvement (HCVI)

August 2007


Abstract:     
Classical parametric tests compare observed statistics to theoretical sampling distributions. Re-sampling is a revolutionary methodology because it departs from theoretical distributions; the inference is based upon repeated sampling within the same empirical sample. This definition encompasses Monte Carlo simulation, cross validation tests, jackknife and bootstrap procedures.
The need for such methods is heightened by the vast amounts of data being collected in the modern information age, and by the increasingly complex scientific questions being asked. These factors have together led to the rapid development of modern non-parametric methods. An appealing feature of re-sampling methods is the way they combine an intuitive and layman-friendly applied aspect with challenging and elegant mathematics.
Purpose of this review is to divulge the theoretical foundations of re-sampling and to facilitate a coherent use of this computational intensive research method.

Number of Pages in PDF File: 36

Keywords: resampling, statistical, method, non-parametric

JEL Classification: C14

working papers series





Download This Paper

Date posted: September 13, 2007  

Suggested Citation

Favato, Giampiero and Mills, Roger, Thinking the Unthinkable: Modern Non-Parametric Re-sampling Methods (August 2007). Available at SSRN: http://ssrn.com/abstract=1012661 or http://dx.doi.org/10.2139/ssrn.1012661

Contact Information

Giampiero Favato (Contact Author)
Kingston University ( email )
Kingston Hill
Kingston upon Thames
Surrey KT2 7LB
United Kingdom
Roger Mills
Henley Management College - Henley Centre for Value Improvement (HCVI) ( email )
Greenlands
Henley-on-Thames
Oxfordshire RG9 3AU, England
United Kingdom
HOME PAGE: www.henleymc.ac.uk/hcvi
Feedback to SSRN


Paper statistics
Abstract Views: 725
Downloads: 100
Download Rank: 162,795
References:  40

© 2014 Social Science Electronic Publishing, Inc. All Rights Reserved.  FAQ   Terms of Use   Privacy Policy   Copyright   Contact Us
This page was processed by apollo1 in 0.297 seconds