Estimating Beta Inverse Weibull Distribution by the Method of Quantile Estimates
M. Faysal Satter. International Journal of Research and Innovation in Applied Science (IJRIAS), 1 (6):
01-05(September 2016)
Abstract
The Beta Inverse Weibull distribution is one of the
widely applied distribution. In reliability and biological studies,
we can model failure rates by this distribution. In this paper, we
extend the study of the Beta Inverse Weibull distribution (BIW).
The unimodal BIW with three parameters are estimated by the
Method of Quantile Estimates (MQE) and then compared with
parameters estimated by the Maximum Likelihood Estimates
(MLE). To estimate the model parameters, Newton-Raphson
method is applied for MLE and Nelder-Mead Simplex method is
applied for MQE and the table of simulation results is shown.
Finally, practical use of the model is demonstrated by dint of an
application to real data. For the real data computation, standard
deviations of the estimated parameters are calculated by random
permutation method.
%0 Journal Article
%1 faysalsatter2016estimating
%A Faysal Satter, Mezbahur Rahman
%D 2016
%J International Journal of Research and Innovation in Applied Science (IJRIAS)
%K IJRIAS RSIS mathematics
%N 6
%P 01-05
%T Estimating Beta Inverse Weibull Distribution by the Method of Quantile Estimates
%U http://www.ijrias.org/DigitalLibrary/Vol.1&Issue6/01-05.pdf
%V 1
%X The Beta Inverse Weibull distribution is one of the
widely applied distribution. In reliability and biological studies,
we can model failure rates by this distribution. In this paper, we
extend the study of the Beta Inverse Weibull distribution (BIW).
The unimodal BIW with three parameters are estimated by the
Method of Quantile Estimates (MQE) and then compared with
parameters estimated by the Maximum Likelihood Estimates
(MLE). To estimate the model parameters, Newton-Raphson
method is applied for MLE and Nelder-Mead Simplex method is
applied for MQE and the table of simulation results is shown.
Finally, practical use of the model is demonstrated by dint of an
application to real data. For the real data computation, standard
deviations of the estimated parameters are calculated by random
permutation method.
@article{faysalsatter2016estimating,
abstract = {The Beta Inverse Weibull distribution is one of the
widely applied distribution. In reliability and biological studies,
we can model failure rates by this distribution. In this paper, we
extend the study of the Beta Inverse Weibull distribution (BIW).
The unimodal BIW with three parameters are estimated by the
Method of Quantile Estimates (MQE) and then compared with
parameters estimated by the Maximum Likelihood Estimates
(MLE). To estimate the model parameters, Newton-Raphson
method is applied for MLE and Nelder-Mead Simplex method is
applied for MQE and the table of simulation results is shown.
Finally, practical use of the model is demonstrated by dint of an
application to real data. For the real data computation, standard
deviations of the estimated parameters are calculated by random
permutation method.},
added-at = {2016-10-13T08:27:20.000+0200},
author = {Faysal Satter, Mezbahur Rahman},
biburl = {https://www.bibsonomy.org/bibtex/262d936977cd63a7ce19077dcea606ac1/ijrias},
interhash = {5447fdb528d7d53bd1cce198ba4d9fc7},
intrahash = {62d936977cd63a7ce19077dcea606ac1},
journal = {International Journal of Research and Innovation in Applied Science (IJRIAS)},
keywords = {IJRIAS RSIS mathematics},
month = {September},
number = 6,
pages = {01-05},
timestamp = {2016-10-13T08:37:48.000+0200},
title = {Estimating Beta Inverse Weibull Distribution by the Method of Quantile Estimates},
url = {http://www.ijrias.org/DigitalLibrary/Vol.1&Issue6/01-05.pdf},
volume = 1,
year = 2016
}