Partial Generalized Probability Weighted Moments for Exponentiated Exponential Distribution

Neema Mohamed El Haroun

Abstract


The generalized probability weighted moments are widely used in hydrology for estimating parameters of flood distributions from complete sample. The method of partial generalized probability weighted moments was used to estimate the parameters of distributions from censored sample. This article offers new method called partial generalized probability weighted moments (PGPWMs) for the analysis of censored data. The method of PGPWMs is an extended class from partial generalized probability weighted moments. To illustrate the new method, estimation of the unknown parameters from exponentiated exponential distribution based on doubly censored sample is considered. PGPWMs estimators for right and left censored samples are obtained as special cases.   Simulation study is conducted to investigate performance of estimates for exponentiated exponential distribution. Comparison between estimators is made through simulation via their biases and  mean square errors. An illustration with real data is provided.

Keywords


Generalized Probability Weighted Moments, Partial Probability Weighted Moments, Partial generalized Probability Weighted Moments, Generalized Exponential Distribution, Censored Samples

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DOI: http://dx.doi.org/10.18187/pjsor.v11i3.729

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Title

Partial Generalized Probability Weighted Moments for Exponentiated Exponential Distribution

Keywords

Generalized Probability Weighted Moments, Partial Probability Weighted Moments, Partial generalized Probability Weighted Moments, Generalized Exponential Distribution, Censored Samples

Description

The generalized probability weighted moments are widely used in hydrology for estimating parameters of flood distributions from complete sample. The method of partial generalized probability weighted moments was used to estimate the parameters of distributions from censored sample. This article offers new method called partial generalized probability weighted moments (PGPWMs) for the analysis of censored data. The method of PGPWMs is an extended class from partial generalized probability weighted moments. To illustrate the new method, estimation of the unknown parameters from exponentiated exponential distribution based on doubly censored sample is considered. PGPWMs estimators for right and left censored samples are obtained as special cases.   Simulation study is conducted to investigate performance of estimates for exponentiated exponential distribution. Comparison between estimators is made through simulation via their biases and  mean square errors. An illustration with real data is provided.

Date

2015-09-08

Identifier


Source

Pakistan Journal of Statistics and Operation Research; Vol. 11 No. 3, 2015



Print ISSN: 1816-2711 | Electronic ISSN: 2220-5810