Hypothesis Testing in Weighted Distributions

Authors

  • Seyed Mohammad Reza Alavi
  • Rahim Chinipardaz
  • Abdorrahman Rasekh

DOI:

https://doi.org/10.30495/jme.v0i0.39

Keywords:

Monotone likelihood ratio, Neyman- Pearson lemma, weighted distributions, UMPU tests, Monte Carlo simulation.

Abstract

There are many situations in which experiments are not available or data are recorded from the population propor- tion to a nonnegative function called weight function. In a such situations the classical methods for inferencing about unknown parameters are not useful. In this study the problem of statisti- cal hypothesis testing is considered for weighted distributions to obtain (uniformly) most powerful tests.

Author Biographies

Seyed Mohammad Reza Alavi

Department of Statistics Shahid Chamran University of Ahvaz Ahvaz, Iran.

Rahim Chinipardaz

Department of Statistics Shahid Chamran University of Ahvaz Ahvaz, Iran.

Abdorrahman Rasekh

Department of Statistics Shahid Chamran University of Ahvaz Ahvaz, Iran.

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Published

2008-03-01

Issue

Section

Vol. 3, No. 1 (2008)