Inference of Process Capability Index Cpy for 3-Burr-XII Distribution Based on Progressive Type-II Censoring by Rashad M. EL-Sagheer, Mustafa M. Hasaballah

“…The Bayesian estimates for the index Cpy have been obtained by the Markov Chain Monte Carlo method. Also, the credible intervals are constructed by using MCMC samples. …”
Get full text

Testing Data Cloning as the Basis of an Estimator for the Stochastic Volatility in Mean Model by E. Romero, E. Ropero-Moriones

“…Notably, the estimates it provides yield superior outcomes than those derived from the Markov chain Monte Carlo (MCMC) method in terms of standard errors, all while being unaffected by the selection of prior distributions.…”
Get full text

Asymmetric Randomly Censored Mortality Distribution: Bayesian Framework and Parametric Bootstrap with Application to COVID-19 Data by Rashad M. EL-Sagheer, Mohamed S. Eliwa, Khaled M. Alqahtani, Mahmoud EL-Morshedy

“…In Bayesian framework, the Bayes estimates of the unknown parameters are evaluated by applying the Markov chain Monte Carlo technique, and highest posterior density credible intervals are also carried out. …”
Get full text

Best Prediction Method for Progressive Type-II Censored Samples under New Pareto Model with Applications by Hanan Haj Ahmad

“…Since Bayes estimators cannot be expressed explicitly, Gibbs and the Markov Chain Monte Carlo techniques are utilized for Bayesian calculation. …”
Get full text

A New Bayesian Network-Based Generalized Weighting Scheme for the Amalgamation of Multiple Drought Indices by Muhammad Ahmad Raza, Mohammed M. A. Almazah, Nadhir Al-ansari, Ijaz Hussain, Fuad S. Al-Duais, Mohammed A. Naser

“…These ADPPs are obtained from Bayesian networks (BNs)-based Markov Chain Monte Carlo (MCMC) simulations. Results have shown that the MWADI correlates more with the standardized precipitation index (SPI) and the standardized precipitation temperature index (SPTI). …”
Get full text

Modeling Repayment Behavior of Consumer Loan in Portfolio across Business Cycle: A Triplet Markov Model Approach by Shou Chen, Xiangqian Jiang

“…The corresponding Markov chain Monte Carlo algorithms of the particular TMM are also developed for estimating the model parameters. …”
Get full text

Bayesian Non-Parametric Mixtures of GARCH(1,1) Models by John W. Lau, Ed Cripps

“…Inference is Bayesian, and a Markov chain Monte Carlo algorithm to explore the posterior distribution is described. …”
Get full text

Statistical Investigation of Bearing Capacity of Pile Foundation Based on Bayesian Reliability Theory by Zuolong Luo, Fenghui Dong

“…In order to improve the estimation accuracy of bearing capacity of pile foundation, a new forecast method of bearing capacity of pile foundation was proposed on Jeffrey’s noninformative prior using the MCMC (Markov chain Monte Carlo) method of the Bayesian theory. The proposed approach was used to estimate the parameters of Normal distribution. …”
Get full text

Within‐chain parallelization—Giving Stan Jet Fuel for population modeling in pharmacometrics by Casey Davis, Pavan Vaddady

“…To perform a Bayesian data analysis, most models in pharmacometrics require Markov Chain Monte Carlo (MCMC) methods to sample from the posterior distribution. …”
Get full text

Estimations in a Constant-Stress Partially Accelerated Life Test for Generalized Rayleigh Distribution under Type-II Hybrid Censoring Scheme by Abdalla Rabie, Eslam Hussam, Abdisalam Hassan Muse, Ramy Abdelhamid Aldallal, Amirah Saeed Alharthi, Hassan M. Aljohani

“…Bayesian and E-Bayesian estimates are obtained using Markov chain Monte Carlo (MCMC) methods. To prove the applicability and the importance of the subject, a test for real data will be provided. …”
Get full text

An Incremental-Hybrid-Yager’s Entropy Model for Dynamic Portfolio Selection with Fuzzy Variable by Yin Li, Jian Tao, Yazhi Song

“…At last, a compromised genetic algorithm is designed, and the numerical example shows that the proposed model achieves solid returns compared against the mean-variance model and Markov chain Monte Carlo method.…”
Get full text

Bayesian Estimation of Archimedean Copula-Based SUR Quantile Models by Nachatchapong Kaewsompong, Paravee Maneejuk, Woraphon Yamaka

“…As there are many parameters to be estimated, we consider the Bayesian Markov chain Monte Carlo approach to estimate the parameter interests in the model. …”
Get full text

Bayesian and non-bayesian analysis for stress-strength model based on progressively first failure censoring with applications. by Salem A Alyami, Amal S Hassan, Ibrahim Elbatal, Olayan Albalawi, Mohammed Elgarhy, Ahmed R El-Saeed

“…It is suggested that Markov chain Monte Carlo techniques be used for Bayesian estimation in order to achieve Bayes estimators and the associated credible intervals. …”
Get full text

Hierarchical Bayesian Spatio-Temporal Modeling for PM10 Prediction by Esam Mahdi, Sana Alshamari, Maryam Khashabi, Alya Alkorbi

“…The disaggregating technique with a Markov chain Monte Carlo method with Gibbs sampler are used to handle the missing data. …”
Get full text

LED Lighting System Reliability Modeling and Inference via Random Effects Gamma Process and Copula Function by Huibing Hao, Chun Su, Chunping Li

“…Considering the model is so complicated and analytically intractable, the Markov chain Monte Carlo (MCMC) method is used to estimate the unknown parameters. …”
Get full text

Using the Bayesian Model Averaging Approach for Genomic Selection by Considering Skewed Error Distributions by Azadeh Ghazanfari, Afshin Fayyaz Movaghar

“…Occam’s window and Markov-Chain Monte Carlo model composition (MC3) were used to determine the best model and its uncertainty. …”
Get full text

Splitting Travel Time Based on AFC Data: Estimating Walking, Waiting, Transfer, and In-Vehicle Travel Times in Metro System by Yong-Sheng Zhang, En-Jian Yao

“…A new estimation model based on Bayesian inference formulation is proposed in this paper by integrating the probability measurement of the OD pair with only one effective route, in which all kinds of times follow the truncated normal distributions. Then, Markov Chain Monte Carlo method is designed to estimate all parameters endogenously. …”
Get full text

A Bayesian Hierarchical Model for Relating Multiple SNPs within Multiple Genes to Disease Risk by Lewei Duan, Duncan C. Thomas

“…The entire model is fitted using Markov chain Monte Carlo methods. Simulation studies show that the approach is capable of recovering many of the truly causal SNPs and genes, depending upon their frequency and size of their effects. …”
Get full text

Estimation of the coefficients of variation for inverse power Lomax distribution by Samah M. Ahmed, Abdelfattah Mustafa

“…Additionally, it is recommended to use the Markov Chain Monte Carlo (MCMC) method to calculate the Bayes estimate and generate posterior distributions. …”
Get full text

Modified Chen distribution: Properties, estimation, and applications in reliability analysis by M. G. M. Ghazal

“…Bayesian estimates of the model parameters, along with the survival and hazard functions and their corresponding credible intervals, were derived via the Markov chain Monte Carlo method under balanced squared error loss, balanced linear-exponential loss, and balanced general entropy loss. …”
Get full text