Title : ( Bootstrap Statistical Inference for the Variance Based on Fuzzy Data )
Authors: Mohammad Ghasem Akbari , Abdolhamid Rezaei Roknabadi ,
Full TextAbstract
The bootstrap is a simple and straightforward method for calculating approximated biases, standard deviations, confidence intervals, testing statistical hypotheses, and so forth, in almost any nonparametric estimation problem. In this paper we describe a bootstrap method for variance that is designed directly for hypothesis testing in case of fuzzy data based on Yao-Wu signed distance.
Keywords
, Fuzzy Canonical Number, Yao-Wu Signed Distance, Confidence Interval, Testing Hypotheses, Degree of Acceptance, Degree of Rejection.
@article{paperid:1020055,
author = {Mohammad Ghasem Akbari and Rezaei Roknabadi, Abdolhamid},
title = {Bootstrap Statistical Inference for the Variance Based on Fuzzy Data},
journal = {Austrian Journal of Statistics},
year = {2009},
volume = {38},
number = {2},
month = {February},
issn = {1026-597X},
pages = {121--130},
numpages = {9},
keywords = {Fuzzy Canonical Number; Yao-Wu Signed Distance; Confidence
Interval; Testing Hypotheses; Degree of Acceptance; Degree of Rejection.},
}
%0 Journal Article
%T Bootstrap Statistical Inference for the Variance Based on Fuzzy Data
%A Mohammad Ghasem Akbari
%A Rezaei Roknabadi, Abdolhamid
%J Austrian Journal of Statistics
%@ 1026-597X
%D 2009
