Metropolis-Hastings
A piecewise deterministic scaling limit of Lifted Metropolis Hastings in the Curie Weiss model
... The main result of this paper may be found in Section 4. In this section, we ob- tain the scaling limit of the magnetization for LMH applied to Curie–Weiss, again for the cases β < 1 (Theorem 3) and β = 1, h = 0 ...
38
Adaptive metropolis Hastings sampling using reversible dependent mixture proposals
... Our article constructs a general-purpose adaptive sampler that we call the Adaptive Correlated Metropolis- Hastings (ACMH) sampler. The sampler is described in Section 4. The first contribution of the ...
23
Estimating GARCH Modeling Using Metropolis Hastings Method in R
... This paper mainly talks about a popular approach of volatility of a GARCH-type model in R, while the disturbances are independent and have identical Student-t distribution. It uses the Metropolis-Hastings ...
8
Log-concave sampling: Metropolis-Hastings algorithms are fast
... Both the ULA and underdamped-Langevin MCMC methods are based on evaluations of the gradient ∇ f , along with the addition of Gaussian noise. Durmus et al. (2019) shows that for an appropriate decaying step size schedule, ...
42
Pseudo marginal Metropolis Hastings sampling using averages of unbiased estimators
... The Metropolis–Hastings algorithm is often used to approximate expectations with respect to posterior distributions, making use of point-wise evaluations of the posterior density π up to a fixed but ...
9
Pseudo marginal Metropolis–Hastings using averages of unbiased estimators
... marginal Metropolis–Hastings algorithm (Beaumont, 2003; Andrieu & Roberts, 2009) can be used if a realisation of a non-negative, unbiased stochastic estimator of the target density, possibly up to an ...
9
Non reversible Metropolis Hastings
... The theoretical discussion of Sect. 3 and the numeri- cal experiment of Sect. 4.4 illustrate how efficiency can be improved by employing non-reversible Metropolis-Hastings. In view of these encouraging ...
17
Stability of noisy Metropolis–Hastings
... In this article, fundamental stability properties of the noisy algorithm have been explored. The noisy Markov ker- nels considered are perturbed Metropolis–Hastings kernels defined by a collection of ...
26
Spectral gaps for a Metropolis–Hastings algorithm in infinite dimensions
... In most infinite dimensional settings, the splitting chain method cannot be ap- plied since measures tend to be mutually singular. The method is hence not well- adapted to the high-dimensional setting. Even Gaussian ...
37
CGMH: Constrained Sentence Generation by Metropolis-Hastings Sampling
... In real-world applications of natural language generation, there are often constraints on the target sentences in addi- tion to fluency and naturalness requirements. Existing lan- guage generation techniques are usually ...
9
Estimating effective population size and mutation rate from sequence data using Metropolis-Hastings sampling.
... The method is somewhat more successful when it begins from a reasonable genealogy (data not shown). Genealogies from the short chains should not be used in the final es[r] ...
10
A Dirichlet form approach to MCMC optimal scaling
... These results lead to optimal scaling arguments for finite-dimensional distributions of the Metropolis–Hastings random walk sampler, directly following the final argument of Roberts et al. [22]. Fastest ...
31
A Bayesian nonlinearity test for threshold moving average models
... Abstract. We propose a Bayesian test for nonlinearity of threshold moving aver- age (TMA) models. First of all, we obtain the marginal posterior densities of all parameters, including the threshold and delay, of TMA ...
16
A Bayesian Inference Approach to Reduce Uncertainty in Magnetotelluric Inversion: A Synthetic Case Study
... The deterministic geophysical inversion methods are dominant when in- verting magnetotelluric data whereby its results largely depends on the as- sumed initial model and only a single representative solution is obtained. ...
14
Random partition models and complementary clustering of Anglo Saxon place names
... We carefully considered the computational aspects of this problem. After con- sidering related problems in the complexity theory literature (see Section 3.6), we employed the Metropolis–Hastings (MH) ...
32
Bayesian inference of ancestral dates on bacterial phylogenetic trees
... MCMC moves, all of which are used by default but can be deactivated by the user: • A Metropolis-Hastings move proposing to update the value of the mean substitution rate • A Gibbs move[r] ...
11
A Bayesian Network for Symptom diagnosis Data
... based Metropolis-Hastings sampling method is introduced to fill in the missing data; Then, a K2 algorithm is used to search for all possible Bayesian networks among the relationship between symptoms and ...
7
Statistical shape analysis for bio structures : local shape modelling, techniques and applications
... Key words: Shape, Statistical Shape Modelling, Local Shape Models, Fractal Dimension, Markov Chain Monte Carlo, Metropolis-Hastings Algorithm, Hierarchical Shape Analysis, Curvature Scal[r] ...
216
A rare event approach to high dimensional approximate Bayesian computation
... Abstract Approximate Bayesian computation (ABC) meth- ods permit approximate inference for intractable likelihoods when it is possible to simulate from the model. However, they perform poorly for high-dimensional data ...
16
A Bayesian approach to inferring vascular tree structure from 2D imagery
... Møller Perfect Metropolis-Hastings simulation of locally stable point processes.. Møller Perfect implementation of a Metropolis-Hastings simulation of Markov point processes 349: with Y.[r] ...
13