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Monte Carlo Markov chain approach

The Sloan Digital Sky Survey Reverberation Mapping Project : accretion disk sizes from continuum lags

The Sloan Digital Sky Survey Reverberation Mapping Project : accretion disk sizes from continuum lags

... a Markov chain Monte Carlo approach, parameterizing the measured continuum lags as a function of disk size normalization, wavelength, black hole mass, and ...Bayesian approach on ...

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Estimation of Admixture Proportions: A Likelihood-Based Approach Using Markov Chain Monte Carlo

Estimation of Admixture Proportions: A Likelihood-Based Approach Using Markov Chain Monte Carlo

... by 1. The waiting time until the next coalescent event p(D|⌿) ⫽ 冮 G,c p(D|G) p(G|c) p(c|⌿)dGdc, (3) is sampled from an exponential distribution (Kingman 1982a,b; Hudson 1990). The equivalent probability un- where G ...

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On Markov chain Monte Carlo methods for tall data

On Markov chain Monte Carlo methods for tall data

... Markov chain Monte Carlo methods are often deemed too computationally intensive to be of any practical use for big data applications, and in particular for inference on datasets containing a ...

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A Novel Markov Chain Monte Carlo Approach for Constructing Accurate Meiotic Maps

A Novel Markov Chain Monte Carlo Approach for Constructing Accurate Meiotic Maps

... linkage approach for ordering many markers jointly on general ...using Monte Carlo sampling to form a Markov chain with pðu; p; d; SjYÞ as its stationary distribu- ...

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The Impact of Monetary Policy on Economic Growth in Cambodia: Bayesian Approach

The Impact of Monetary Policy on Economic Growth in Cambodia: Bayesian Approach

... This research paper aims to study the significance of monetary policy in the contribution to the economic growth of Cambodia. This study employs the data in the period of 2000-2018 consisting in total 19 years. Once the ...

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A Bayesian Approach to Detect Quantitative Trait Loci Using Markov Chain Monte Carlo

A Bayesian Approach to Detect Quantitative Trait Loci Using Markov Chain Monte Carlo

... Using a Bayesian approach a multi-locus model is fit to quantitative trait and molecular marker data, instead of fitting one locus at a time.. The phenotypic trai[r] ...

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Distinguishing Migration From Isolation: A Markov Chain Monte Carlo Approach

Distinguishing Migration From Isolation: A Markov Chain Monte Carlo Approach

... The estimator of T does not appear to have similarly desirable properties, at least not in the case of T ⫽ ∞. There are two reasons for this. First, the Monte Carlo variance for the parameter T seems to be ...

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Cascade source inference in networks: a Markov chain Monte Carlo approach

Cascade source inference in networks: a Markov chain Monte Carlo approach

... Cascades of information, ideas, rumors, and viruses spread through networks. Sometimes, it is desirable to find the source of a cascade given a snapshot of it. In this paper, source inference problem is tackled under ...

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Stochastic gradient Markov chain Monte Carlo

Stochastic gradient Markov chain Monte Carlo

... As discussed in Section 2.5 with regard to SGLD, re-parameterising the target distribution so that the components of θ are roughly uncorrelated and have similar marginal variances, can improve mixing. An extension of ...

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A fully Bayesian approach to shape estimation of objects from tomography data using MFS forward solutions

A fully Bayesian approach to shape estimation of objects from tomography data using MFS forward solutions

... this approach to electrical impedance tomography (EIT), see West et ...alternative approach is ...the Markov chain Monte Carlo (MCMC) method presented – for a detailed ...

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Sparse Estimation in Ising Model via Penalized Monte Carlo Methods

Sparse Estimation in Ising Model via Penalized Monte Carlo Methods

... instance Markov random fields (Banerjee et ...pseudolikelihood approach (Besag, 1974) that is replacing the likelihood (that contains the norming constant) by the product of conditionals (that do not ...

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Localisation of an Unknown Number of Land Mines Using a Network of Vapour Detectors

Localisation of an Unknown Number of Land Mines Using a Network of Vapour Detectors

... used approach for estimating the properties of the posterior distribution given in (18) is to perform Markov chain Monte Carlo (MCMC) sampling ...a Markov chain where each ...

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Copula Gaussian graphical modelling of biological networks and Bayesian inference of model parameters

Copula Gaussian graphical modelling of biological networks and Bayesian inference of model parameters

... Jump Markov Chain Monte Carlo (RJMCMC) approach as another alterna- tive to the birth-and-death (BDMCMC) algorithm for CGGM is implemented ...RJMCMC approach has been adopted to ...

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Information geometric Markov chain Monte Carlo methods using diffusions

Information geometric Markov chain Monte Carlo methods using diffusions

... straight-forward approach is to define proposals for which the prior is invariant, since the likelihood contribution to the posterior typically will not alter its support from that of the prior ...

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Stability of sequential Markov Chain Monte Carlo methods

Stability of sequential Markov Chain Monte Carlo methods

... the Monte Carlo estimators as N → ...inequality approach enables us to prove stability properties not only under global but also under local conditions, ...

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Uncovering mental representations with Markov chain Monte Carlo

Uncovering mental representations with Markov chain Monte Carlo

... our approach is to design a procedure that produces samples of stimuli that are not chosen before the experiment begins, but are adaptively selected to concentrate in regions where the function in question has ...

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Geostatistical approach to bayesian inversion of geophysical data: Markov chain Monte Carlo method

Geostatistical approach to bayesian inversion of geophysical data: Markov chain Monte Carlo method

... Geostatistics was originally devised to estimate properties of unsampled points for delineating ore deposits. But these days those tools are used not only for estimation of unsam- pled points but also for inference of ...

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MODELLING OF STOCK PRICES BY THE MARKOV CHAIN MONTE CARLO METHOD

MODELLING OF STOCK PRICES BY THE MARKOV CHAIN MONTE CARLO METHOD

... e Markov chain Monte Carlo method is used to sample from empirical prob- ability density of a stock ...this approach of modelling stock ...

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Markov chain monte carlo algorithm for bayesian policy search

Markov chain monte carlo algorithm for bayesian policy search

... a Markov chain Monte Carlo (MCMC) ...Sequential Monte Carlo (SMC), also known as particle filters, within its learning ...of Monte Carlo algorithms in which the ...

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Markov Chain Monte Carlo Technology

Markov Chain Monte Carlo Technology

... One approach for determining sampler performance and the size of the burn-in time is to employ analytical methods to the specified Markov chain, prior to ...This approach is exemplified in the ...

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