Questions tagged [reversible-jump]
Reversible jump MCMC is a Markov chain Monte Carlo method designed to move between spaces of different dimensions while preserving the intended target distribution.
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Reversible-jump MCMC for knot selection
Let $\{Z(\boldsymbol s):\boldsymbol s\in\mathcal D\}$ denote the Gaussian spatial random field on a spatial domain $\mathcal D\subset\mathbb R^2$.
Suppose that at $N$ locations, we have observations $\...
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Model Comparison within Bayesian Gaussian Mixture Model framework
Suppose that we conduct a simulation study, and the model that generated the data is the following Gaussian Mixture Model.
$$f(x)=\pi_{1}N(x;\mu_{1},\sigma_{1}^{2})+\pi_{2}N(x;\mu_{2},\sigma_{2}^{2})+\...
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What is a perfect distribution to consider for the step increase/ decrease for the reversible jump MCMC
I am trying to understand the hyper parameters in the paper [1] for the model order selection with reversible jump MCMC (RJ-MCMC). There is a hyper parameter $\Lambda$ (The parameter of the Poisson ...
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Simple alternative to reversible jump for nested models?
Suppose that we have a model such that $p(y\mid k, \theta_1,\dots,\theta_{k_\text{max}})$ depends only on $k,\theta_1,\dots,\theta_k$. Hence, as $k$ assumes the values $1,\dots,k_\text{max}$, we have ...
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BMA and RJMCMC predictive performance
We have a family of statistical models, with parameter spaces of different dimensions, which we aggregated through standard Bayesian Model Averaging (BMA). Experiments using training and test sets ...
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Reversible Jump for normal mixtures in R^d
I'm reading the article "Multivariate mixtures of normals with unknown number of
components" (Dellaportas and Papageorgiou 2006).
In this article they describe in great details how to ...
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How to calculate the MH ratio in a birth-death Reversible Jump MCMC?
I know the formula and think I understand it, but I must be doing something wrong.
Assume $J\sim po(\lambda)$ and $X_J=(U_1, \dots, U_J)$ and $U_i\sim U(0,w)$. Then I want to sample from the ...
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A question about the choice and interpretation of the jumping distribution in Metropolis-Hastings algorithm
In order to implement the MH algorithm you need a proposal density or jumping distribution $q(⋅|⋅)$, from which it is easy to sample. If you want to sample from a distribution $f(⋅)$, the MH algorithm ...
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Gibbs sampling with mixed prior using a Metropolis-Hastings step
My questions are about a sampling procedure for fitting a Bayesian hierarchical model where one of the priors is a mixture distribution of discrete and continuous parts. The model is not my own but I ...
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