Analysis of Block Adaptive Type-II Progressive Hybrid Censoring with Weibull Distribution by Kundan Singh, Yogesh Mani Tripathi, Liang Wang, Shuo-Jye Wu

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A new generalized inverse Gaussian distribution with Bayesian estimators by Kenneth Goward, Chin-I Cheng, Kahadawala Cooray, Keshab Raj Dahal

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Bayesian Estimation for Zero-Truncated Bivariate Poisson Regression Model by Prapaporn Rerngchaiyaphum, Monthira Duangsaphon

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Statistical Inference for Two Lomax Populations Under Balanced Joint Progressive Type-II Censoring Scheme by Yuanqi Wang, Jinchen Xiang, Wenhao Gui

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BAYESIAN PARAMETER ESTIMATION OF WEIBULL DISTRIBUTION WITH MULTIPLE CHANGE POINTS FOR RANDOM CENSORING TEST MODEL WITH INCOMPLETE INFORMATION by HE ChaoBing

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An Algorithm for the Conditional Distribution of Independent Binomial Random Variables Given the Sum by Kelly Ayres, Steven E. Rigdon

Subjects: “…random walk metropolis–hastings algorithm…”
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Bayesian Quantile Regression for Partial Functional Linear Spatial Autoregressive Model by Dengke Xu, Shiqi Ke, Jun Dong, Ruiqin Tian

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Improving Bayesian Model Averaging for Ensemble Flood Modeling Using Multiple Markov Chains Monte Carlo Sampling by Tao Huang, Venkatesh Merwade

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Reliability Estimation for the Gull Alpha Power Pareto Model Under Progressive Type-I Censoring by Mahmoud M. Abdelwahab, Ahmed R. El-Saeed, M. A. Abdelkawy, Mohamed Khalifa Ahmed Issa, Hanem Mohamed

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Estimating the Lifetime Parameters of the Odd-Generalized-Exponential–Inverse-Weibull Distribution Using Progressive First-Failure Censoring: A Methodology with an Application by Mahmoud M. Ramadan, Rashad M. EL-Sagheer, Amel Abd-El-Monem

Subjects: “…Gibbs sampler within Metropolis–Hasting algorithm…”
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Adjustment Cost on Investment and Under-Utilization of Maximum Installed Capacity in South Korean Business Cycle - A Bayesian New Keynensian Model by Al Mamun Tuhin G M, Ehsanullah

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Calibration and Uncertainty Analysis of Freundlich and Langmuir Isotherms Using the Markov Chain Monte Carlo (MCMC) Approach by Haniyeh Sharifi Moghadam, Saeed Alimohammadi

“…This study highlights the superiority of the Langmuir model and the Metropolis-Hastings algorithm in adsorption data analysis and uncertainty evaluation.…”
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Bayesian Adaptive Lasso for the Partial Functional Linear Spatial Autoregressive Model by Dengke Xu, Ruiqin Tian, Ying Lu

“…With approximating to the functional coefficient by Karhunen–Loève representation, we propose a Bayesian adaptive Lasso method to simultaneously estimate unknown parameters and select important covariates in the model, which can be performed by combining the Gibbs sampler and the Metropolis–Hastings algorithm. Some simulation studies are conducted and the results show that the proposed Bayesian method behaves well.…”
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Bayesian Adaptive Lasso for Regression Models with Nonignorable Missing Responses by Yuanying Zhao, Xingde Duan

“…A sampling procedure combining the Gibbs sampler and Metropolis-Hastings algorithm is employed to obtain the Bayesian estimates of the regression coefficients, shrinkage coefficients, missingness mechanism models parameters, and their standard errors. …”
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Estimation of Spatially Varying Parameters with Application to Hyperbolic SPDES by David Angwenyi

“…We use the Metropolis-Hastings algorithm as a selection criterion for the maximum filter likelihood. …”
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On the Flexible Alpha Skew-logistic Distribution: Properties and Applications by Jondeep Das, Partha Hazarika, G. G. Hamedani, Morad Alizadeh, Javier Contreras-Reyes

“…The study also includes a simulation study using the Metropolis--Hastings algorithm to observe the behavior of the estimated parameters. …”
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Estimation and Bayesian Prediction of the Generalized Pareto Distribution in the Context of a Progressive Type-II Censoring Scheme by Tianrui Ye, Wenhao Gui

“…Bayesian estimations are conducted using the Tierney and Kadane method alongside the Metropolis–Hastings algorithm, and the highest posterior density credible interval estimation is accomplished. …”
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Covid-19 News Clustering using MCMC-Based Learing of finite EMSD Mixture Models by xuanbo su, Nizar Bouguila, Nuha Zamzami

“…Thus, in this paper, we present a Bayesian learning method based on Markov Chain Monte Carlo and Metropolis-Hastings algorithm for learning this model parameters. …”
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Bayesian inference for dependent stress–strength reliability of series–parallel system based on copula by Li Zhang, Rongfang Yan, Junrui Wang

“…Bayesian estimations are performed using the highly flexible Gamma-Beta prior distribution under different loss functions, and the highest posterior density interval is obtained via the Metropolis-Hastings algorithm. To assess the performance of the proposed methods, Monte Carlo simulations are conducted. …”
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An Ising Spin-Based Model to Explore Efficient Flexibility in Distributed Power Systems by Francisco Prieto-Castrillo, Amin Shokri Gazafroudi, Javier Prieto, Juan Manuel Corchado

“…To this end, a modified version of the Metropolis-Hastings algorithm was implemented, including a gradient descent through the constraint surface. …”
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