A NONPARAMETRIC HYPOTHESIS TEST VIA THE BOOTSTRAP RESAMPLING

This paper adapts an already existing nonparametric hypothesis test to the bootstrap framework. The test utilizes the nonparametric kernel regression method to estimate a measure of distance between the models stated under the null hypothesis. The bootstraped version of the test allows to approximate errors involved in the asymptotic hypothesis test.


Issue Date:
2001
Publication Type:
Conference Paper/ Presentation
PURL Identifier:
http://purl.umn.edu/20600
Total Pages:
18
JEL Codes:
C12; C14; C15
Series Statement:
Selected Paper




 Record created 2017-04-01, last modified 2017-08-24

Fulltext:
Download fulltext
PDF

Rate this document:

Rate this document:
1
2
3
 
(Not yet reviewed)