Open AccessAn algebraic aspect of Pareto mixture parameter estimation using censored sample: A Bayesian approach
Author(s) -
M. Saleem,
Kashif Sharif,
Aliya Fahmi
Publication year - 2018
Publication title -
journal of integrative neuroscience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.336
H-Index - 33
eISSN - 1757-448X
pISSN - 0219-6352
DOI - 10.3233/jin-180082
Subject(s) - pareto distribution , conjugate prior , estimator , prior probability , bayes estimator , bayes' theorem , pareto principle , mathematics , statistics , fisher information , population , feature (linguistics) , sample size determination , mean squared error , bayesian probability , linguistics , philosophy , demography , sociology
Applications of Pareto distribution are common in reliability, survival and financial studies. In this paper, A Pareto mixture distribution is considered to model a heterogeneous population comprising of two subgroups. Each of two subgroups is characterized by the same functional form with unknown distinct shape and scale parameters. Bayes estimators have been derived using flat and conjugate priors using squared error loss function. Standard errors have also been derived for the Bayes estimators. An interesting feature of this study is the preparation of components of Fisher Information matrix.