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Speeding Up MCMC by Efficient Data Subsampling

Quiroz, Matias - 2015

The computing time for Markov Chain Monte Carlo (MCMC) algorithms can be prohibitively large for datasets with many observations, especially when the data density for each observation is costly to evaluate. We propose a framework where the likelihood function is estimated from a random subset of...

Persistent link: https://www.econbiz.de/10013024606

Automated Sensitivity Analysis for Bayesian Inference via Markov Chain Monte Carlo : Applications to Gibbs Sampling

Jacobi, Liana - 2018

Bayesian inference relies heavily on numerical Markov chain Monte carlo (MCMC) methods for the estimation of the …

Persistent link: https://www.econbiz.de/10012933783

Revisiting estimation methods for spatial econometric interaction models

Dargel, Lukas - 2021

Persistent link: https://www.econbiz.de/10012650667

Bayesian estimation and prediction based on Rayleigh record data with applications

Abu Awwad, Raed R.; Bdair, Omar M.; Abufoudeh, Ghassan K. - In: Statistics in transition : an international journal of … 22 (2021) 3, pp. 59-79

Based on a record sample from the Rayleigh model, we consider the problem of estimating the scale and location parameters of the model and predicting the future unobserved record data. Maximum likelihood and Bayesian approaches under different loss functions are used to estimate the model's...

Persistent link: https://www.econbiz.de/10012655797

Performance of MS-GARCH models : Bayesian MCMC-based estimation

Xaba, Lawrence Diteboho; Moroke, Ntebogang Dinah; … - In: Handbook of research on emerging theories, models, and …, (pp. 323-356). 2021

In this chapter, both Maximum likelihood estimation (MLE) and Bayesian MCMC estimation methods are used to test their … parameters estimation power while estimating a Markov-Switching generalized autoregressive conditional heteroscedasticity (MS …. MS(2)-GARCH (1,1) is estimated using both the MLE and Bayesian MCMC. For both methods of estimation, the models were …

Persistent link: https://www.econbiz.de/10012604264