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Questions tagged [metropolis-hastings]

A special type of Markov Chain Monte Carlo (MCMC) algorithm used to simulate from complex probability distributions. It is validated by Markov chain theory and offers a wide range of possible implementations.

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For very basic Metropolis Algorithm with one parameter, what happens when you are at the tail?

I'm not sure how to phrase the question, but let's say you are running the Metropolis Algorithm and the distribution you are trying to produce is just a single distribution. Let's say the values of ...
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Sampling from/near boundary of a region in R^n

Suppose $\Omega$ is a region in $\mathbb R^n$, and suppose we are given a function $\chi(x)$ with $\chi(x)=1$ if $x\in \Omega$ and $\chi(x)=0$ otherwise. If it helps we can assume $\Omega\subseteq B$ ...
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Variance reduction of an estimator arising from the marginal destribution of a Metropolis-Hastings chain

Let $(E,\mathcal E,\lambda)$ and $(E',\mathcal E',\lambda')$ be measure spaces $f\in L^2(\lambda)$ $I$ be a finite nonempty set $\varphi_i:E'\to E$ be bijective $(\mathcal E',\mathcal E)$-measurable ...
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Pareto optimality in Metropolis sampling

In the Metropolis sampling algorithm, we have some function $f(x)$ proportional to a probability distribution $P(x)$. To generate a random walk with stationary distribution $P(x)$, we generate a ...
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Reconciling Langevin MC methods as one-step HMC versus as diffusion or brownian motion

I have a basic understanding of Hamiltonian monte carlo and why it works. I've read that Langevin MC is basically a special case of HMC when you only step the dynamics forward a single timestep before ...
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In the context of a MCMC: how to create/interpret a trace for a matrix?

In a Metropolis-Hastings algorithm, I'm drawing a matrix from a proposal. The accepted matrices should constitute draws from a posterior. If it were just a parameter, I would know how to interpret ...
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slice sampling correctness

Theoretically, the slice sampling has equilibrium distribution as the target distribution. If we can sample exactly as follows, $y' = U(0, p^*(x))$ $x' = U\{x: p^*(x) > y' \}$ However, in the ...
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Metropolis-Hastings algorithm for autocorrelated data

I have auto-correlated data and I wish to apply the Metropolis-Hastings algorithm on it. The data was obtained by simulating the time evolution of a system, and computing the values of some magnitude ...
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Convergence in total distribution distance in the Random Walk Metropolis-Hastings algorithm

I'm searching for a proof of the convergence in total distribution distance of the transition probabilities of a Markov chain generated by the Random Walk Metropolis-Hastings algorithm to its ...
In the famous paper Weak Convergence and Optimal Scaling of Random Walk Metropolis Algorithms by Roberts, Gelman and Gilks, at the bottom of page 116, the supremum of the third derivative of $\ln f$ ...