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Paper Information

Journal:   JOURNAL OF MATHEMATICAL EXTENSION   2008 , Volume 3 , Number 1; Page(s) 55 To 69.
 
Paper: 

HYPOTHESIS TESTING IN WEIGHTED DISTRIBUTIONS

 
 
Author(s):  ALAVI SEYED MOHAMMAD REZA, CHINIPARDAZ RAHIM, RASEKH ABDOLRAHMAN
 
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Abstract: 

There are many situations in which experiments are not available or data are recorded from the population proportion 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 statistical hypothesis testing is considered for weighted distributions to obtain (uniformly) most powerful tests.

 
Keyword(s): MONOTONE LIKELIHOOD RATIO, NEYMAN-PEARSON LEMMA, WEIGHTED DISTRIBUTIONS, UMPU TESTS, MONTE CARLO SIMULATION
 
 
References: 
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Citations: 
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APA: Copy

ALAVI, S., & CHINIPARDAZ, R., & RASEKH, A. (2008). HYPOTHESIS TESTING IN WEIGHTED DISTRIBUTIONS. JOURNAL OF MATHEMATICAL EXTENSION, 3(1), 55-69. https://www.sid.ir/en/journal/ViewPaper.aspx?id=326873



Vancouver: Copy

ALAVI SEYED MOHAMMAD REZA, CHINIPARDAZ RAHIM, RASEKH ABDOLRAHMAN. HYPOTHESIS TESTING IN WEIGHTED DISTRIBUTIONS. JOURNAL OF MATHEMATICAL EXTENSION. 2008 [cited 2021October19];3(1):55-69. Available from: https://www.sid.ir/en/journal/ViewPaper.aspx?id=326873



IEEE: Copy

ALAVI, S., CHINIPARDAZ, R., RASEKH, A., 2008. HYPOTHESIS TESTING IN WEIGHTED DISTRIBUTIONS. JOURNAL OF MATHEMATICAL EXTENSION, [online] 3(1), pp.55-69. Available: https://www.sid.ir/en/journal/ViewPaper.aspx?id=326873.



 
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