نتایج جستجو برای: metropolis hastings algorithm
تعداد نتایج: 759316 فیلتر نتایج به سال:
The simulated annealing algorithm is modified to incorporate a generalization of the Metropolis sampling procedure previously applied to homogenous Markov chains by Hastings[8]. In this report, the inhomogenous version of Hastings' procedure is shown to converge asymptotically under conditions similar to Geman and Geman's logarithmic cooling schedule[7]. The new algorithm is experimentally show...
Here, we work on the problem of point estimation of the parameters of the Poisson-exponential distribution through the Bayesian and maximum likelihood methods based on complete samples. The point Bayes estimates under the symmetric squared error loss (SEL) function are approximated using three methods, namely the Tierney Kadane approximation method, the importance sampling method and the Metrop...
Importance Sampling (IS) is a well-known Monte Carlo technique that approximates integrals involving a posterior distribution by means of weighted samples. In this work, we study the assignation of a single weighted sample which compresses the information contained in a population of weighted samples. Part of the theory that we present as Group Importance Sampling (GIS) has been employed implic...
In this paper, we study a special case of the Metropolis algorithm, the Independence Metropolis Sampler (IMS), in the finite state space case. The IMS is often used in designing components of more complex Markov Chain Monte Carlo algorithms. We present new results related to the first hitting time of individual states for the IMS. These results are expressed mostly in terms of the eigenvalues o...
When doing stochastic modeling one often face the problem of sampling from a posterior pdf on the form const l p where the normalizing constant is unknown The corresponding likelihood function l tends to be complicated and computational expensive while the prior p tends to be simpler This work origin from stochastic reservoir charac terization and history matching where calculation of the likel...
We consider Markov chain Monte Carlo algorithms which combine Gibbs updates with Metropolis-Hastings updates, resulting in a conditional Metropolis-Hastings sampler (CMH). We develop conditions under which the CMH will be geometrically or uniformly ergodic. We illustrate our results by analysing a CMH used for drawing Bayesian inferences about the entire sample path of a diffusion process, base...
A study of principle is conducted on the inclusion of the fermionic determinant as a Metropolis acceptance correction. It is carried out in the 2-D Schwinger model to prepare later applications to the Schrödinger functional. A mixed stochastic/determistic acceptance step is found that allows to include some problematic modes in a way to avoid the collapse of the acceptance rate due to fluctuati...
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Sydney, like all cities, is imagined in particular ways which derive from a specific sociocultural and historical context and which persist over time, even when social and economic changes render the dominant imaginary outmoded. How a city is imagined has distinct effects on how that city is planned and lived, and in this sense a mismatch between the dominant imaginary and the material reality ...
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