IJMLC 2013 Vol.3(1): 21-23 ISSN: 2010-3700
DOI: 10.7763/IJMLC.2013.V3.265

Fuzzy Bootstrap Test for the Mean and Variance with Dp,q-Distance

Bahram Sadeghpour Gildeh and Sedigheh Rahimpour

Abstract—Testing statistical hypothesis is a main topic in statistical inference. In this paper, we consider the problem of testing a simple hypothesis about the mean and variance of a fuzzy random variable with the help of Dp,q-distance. Concerning the hypothesis testing, the bootstrap techniques have empirically shown to be efficient and powerful. By means of simulation and some examples we show that the bootstrap method is a powerful tool in the statistical hypothesis testing about the parameters of fuzzy random variables.

Index Terms—Bootstrap, Dp,q-distance, fuzzy random variable, testing of hypothesis.

The authors are with Department of Statistics, University of Mazandaran, Babolsar, Iran (e-mail: sadeghpour@umz.ac.ir; rahimpour.s@gmail.com).

[PDF]

Cite:Bahram Sadeghpour Gildeh and Sedigheh Rahimpour, "Fuzzy Bootstrap Test for the Mean and Variance with Dp,q-Distance," International Journal of Machine Learning and Computing vol. 3, no. 1, pp. 21-23, 2013.

General Information

  • ISSN: 2010-3700 (Online)
  • Abbreviated Title: Int. J. Mach. Learn. Comput.
  • Frequency: Bimonthly
  • DOI: 10.18178/IJMLC
  • Editor-in-Chief: Dr. Lin Huang
  • Executive Editor:  Ms. Cherry L. Chen
  • Abstracing/Indexing: Scopus (since 2017), EI (INSPEC, IET), Google Scholar, Crossref, ProQuest, Electronic Journals Library.
  • E-mail: ijmlc@ejournal.net