Hypothesis Testing in Weighted Distributions

Seyed Mohammad Reza Alavi, Rahim Chinipardaz, Abdorrahman Rasekh

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.

Keywords


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

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