A weighted version of Gamma distribution

Kanchan Jain; Neetu Singla; Rameshwar D. Gupta

Discussiones Mathematicae Probability and Statistics (2014)

  • Volume: 34, Issue: 1-2, page 89-111
  • ISSN: 1509-9423

Abstract

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Weighted Gamma (WG), a weighted version of Gamma distribution, is introduced. The hazard function is increasing or upside-down bathtub depending upon the values of the parameters. This distribution can be obtained as a hidden upper truncation model. The expressions for the moment generating function and the moments are given. The non-linear equations for finding maximum likelihood estimators (MLEs) of parameters are provided and MLEs have been computed through simulations and also for a real data set. It is observed that WG fits better than its submodels (WE), Generalized Exponential (GE), Weibull and Exponential distributions.

How to cite

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Kanchan Jain, Neetu Singla, and Rameshwar D. Gupta. "A weighted version of Gamma distribution." Discussiones Mathematicae Probability and Statistics 34.1-2 (2014): 89-111. <http://eudml.org/doc/270808>.

@article{KanchanJain2014,
abstract = {Weighted Gamma (WG), a weighted version of Gamma distribution, is introduced. The hazard function is increasing or upside-down bathtub depending upon the values of the parameters. This distribution can be obtained as a hidden upper truncation model. The expressions for the moment generating function and the moments are given. The non-linear equations for finding maximum likelihood estimators (MLEs) of parameters are provided and MLEs have been computed through simulations and also for a real data set. It is observed that WG fits better than its submodels (WE), Generalized Exponential (GE), Weibull and Exponential distributions.},
author = {Kanchan Jain, Neetu Singla, Rameshwar D. Gupta},
journal = {Discussiones Mathematicae Probability and Statistics},
keywords = {gamma distribution; weight function; hazard function; maximum likelihood estimator; Akaike Information criterion; Akaike information criterion},
language = {eng},
number = {1-2},
pages = {89-111},
title = {A weighted version of Gamma distribution},
url = {http://eudml.org/doc/270808},
volume = {34},
year = {2014},
}

TY - JOUR
AU - Kanchan Jain
AU - Neetu Singla
AU - Rameshwar D. Gupta
TI - A weighted version of Gamma distribution
JO - Discussiones Mathematicae Probability and Statistics
PY - 2014
VL - 34
IS - 1-2
SP - 89
EP - 111
AB - Weighted Gamma (WG), a weighted version of Gamma distribution, is introduced. The hazard function is increasing or upside-down bathtub depending upon the values of the parameters. This distribution can be obtained as a hidden upper truncation model. The expressions for the moment generating function and the moments are given. The non-linear equations for finding maximum likelihood estimators (MLEs) of parameters are provided and MLEs have been computed through simulations and also for a real data set. It is observed that WG fits better than its submodels (WE), Generalized Exponential (GE), Weibull and Exponential distributions.
LA - eng
KW - gamma distribution; weight function; hazard function; maximum likelihood estimator; Akaike Information criterion; Akaike information criterion
UR - http://eudml.org/doc/270808
ER -

References

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