Bayesian Analysis of Weighted Boltzmann Maxwell Distribution; a Simulation Study

2021 ◽  
Vol 10 (3) ◽  
pp. 795-806
Keyword(s):  
Bayesian Analysis ◽  
Simulation Study ◽  
Maxwell Distribution

scholarly journals On Bayesian Analysis of Burr Type VII Distribution under Different Censoring Schemes

2012 ◽  
Vol 2012 ◽  
pp. 1-5
Author(s):  
Navid Feroze ◽  
Muhammad Aslam
Keyword(s):  
Comparative Study ◽  
Bayesian Analysis ◽  
Simulation Study ◽  
Type Ii ◽  
Posterior Distributions ◽  
Bayes Estimators ◽  
Type Ii Censoring ◽  
The Comparative Study ◽  
Posterior Estimation

This paper includes the Bayesian analysis of Burr type VII distribution. Three censoring schemes, namely, left censoring, singly type II censoring, and doubly type II censoring have been used for posterior estimation. The results of different censoring schemes have been compared with those under complete samples. The comparative study among the performance of different censoring schemes has also been made. Two noninformative (uniform and Jeffreys) priors have been assumed to derive the posterior distributions under each case. The performance of Bayes estimators has been compared in terms of posterior risks under a simulation study.

scholarly journals Bayesian Analysis for a Fractional Population Growth Model

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Francisco J. Ariza-Hernandez ◽  
Jorge Sanchez-Ortiz ◽  
Martin P. Arciga-Alejandre ◽  
Luis X. Vivas-Cruz
Keyword(s):  
Inverse Problem ◽  
Population Growth ◽  
Bayesian Analysis ◽  
Growth Model ◽  
Simulation Study ◽  
Bayes Factor ◽  
Real Data ◽  
Growth Data ◽  
Fractional Model ◽  
Inversion Theory

We implement the Bayesian statistical inversion theory to obtain the solution for an inverse problem of growth data, using a fractional population growth model. We estimate the parameters in the model and we make a comparison between this model and an exponential one, based on an approximation of Bayes factor. A simulation study is carried out to show the performance of the estimators and the Bayes factor. Finally, we present a real data example to illustrate the effectiveness of the method proposed here and the pertinence of using a fractional model.

scholarly journals Robust Bayesian Analysis of Lifetime Data from Maxwell Distribution

2018 ◽  
Vol 48 (1) ◽  
pp. 38-55
Author(s):  
M. S. Panwar ◽  
Sanjeev K Tomer
Keyword(s):  
Bayesian Analysis ◽  
Real Data ◽  
Type I ◽  
Lifetime Data ◽  
Maxwell Distribution ◽  
Data Set ◽  
Squared Error ◽  
Robust Bayesian Analysis ◽  
Linex Loss ◽  
Mean Lifetime

In this paper, we consider robust Bayesian analysis of lifetime data from the Maxwell distribution assuming an $\varepsilon$-contamination class of prior distributions for the parameter. We obtain robust Bayes estimates of the parameter and mean lifetime under squared error and LINEX loss functions in presence of uncensored as well as Type-I progressively hybrid censored lifetime data. A real data set is analysed for numerical illustrations.

scholarly journals On estimation of Frechet distribution with known shape using Bayesian analysis under informative priors

2017 ◽  
Vol 5 (2) ◽  
pp. 141
Author(s):  
Wajiha Nasir
Keyword(s):  
Bayesian Analysis ◽  
Loss Function ◽  
Simulation Study ◽  
Posterior Distribution ◽  
Loss Functions ◽  
Quadratic Loss ◽  
Bayes Estimators ◽  
Informative Priors ◽  
Fréchet Distribution ◽  
Frechet Distribution

In this study, Frechet distribution has been studied by using Bayesian analysis. Posterior distribution has been derived by using gamma and exponential. Bayes estimators and their posterior risks has been derived using five different loss functions. Elicitation of hyperparameters has been done by using prior predictive distributions. Simulation study is carried out to study the behavior of posterior distribution. Quasi quadratic loss function and exponential prior are found better among all.

scholarly journals An Extended Lindley Distribution with Application to Lifetime Data with Bayesian Estimation

2021 ◽  
Vol 9 (4) ◽  
pp. 849-870
Author(s):  
Morad Alizadeh ◽  
Vahid Ranjbar ◽  
Abbas Eftekharian ◽  
Omid Kharazmi
Keyword(s):  
Bayesian Analysis ◽  
Gibbs Sampling ◽  
Simulation Study ◽  
Asymptotic Properties ◽  
Data Sets ◽  
Lifetime Data ◽  
Lindley Distribution ◽  
Hazard Functions ◽  
Distribution Parameters ◽  
High Flexibility

A four-parameter extended of Lindley distribution with application to lifetime data is introduced.It is called extended Marshal-Olkin generalized Lindley distribution. Some mathematical propertiessuch as moments, skewness, kurtosis and extreme value are derived. These properties with plotsof density and hazard functions are shown the high flexibility of the mentioned distribution. Themaximum likelihood estimations of proposed distribution parameters with asymptotic properties ofthese estimations are examined. A simulation study to investigate the performance of maximumlikelihood estimations is presented. Moreover, the performance and flexibility of the new distributionare investigated by comparing with several generalizations of Lindley distribution through two realdata sets. Finally, Bayesian analysis and efficiency of Gibbs sampling are provided based on the tworeal data sets.

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