نتایج جستجو برای: markov chain algorithm

تعداد نتایج: 1061872  

Journal: :مجله علوم آماری 0
محمدرضا فریدروحانی mohammad reza farid rohani department of statistics, shahid beheshti university, tehran, iran.گروه آمار، دانشگاه شهید بهشتی خلیل شفیعی هولیقی khalil shafiei holighi department of statistics, shahid beheshti university, tehran, iran.گروه آمار، دانشگاه شهید بهشتی

in recent years, some statisticians have studied the signal detection problem by using the random field theory. in this paper we have considered point estimation of the gaussian scale space random field parameters in the bayesian approach. since the posterior distribution for the parameters of interest dose not have a closed form, we introduce the markov chain monte carlo (mcmc) algorithm to ap...

Journal: :IEEE Trans. Information Theory 2000
Christophe Andrieu Arnaud Doucet

Hidden Markov models are mixture models in which the populations from one observation to the next are selected according to an unobserved finite state-space Markov chain. Given a realization of the observation process, our aim is to estimate both the parameters of the Markov chain and of the mixture model in a Bayesian framework. In this paper, we present an original simulated annealing algorit...

2006
GIACOMO ALETTI

Given a strongly stationary Markov chain and a finite set of stopping rules, we prove the existence of a polynomial algorithm which projects the Markov chain onto a minimal Markov chain without redundant information. Markov complexity is hence defined and tested on some classical problems.

Bahman Esmaeili Fraydoon Rahnamay Roodposhti Hamid Vaezi Ashtiani

Investors use different approaches to select optimal portfolio. so, Optimal investment choices according to return can be interpreted in different models. The traditional approach to allocate portfolio selection called a mean - variance explains. Another approach is Markov chain. Markov chain is a random process without memory. This means that the conditional probability distribution of the nex...

2006
GIACOMO ALETTI G. ALETTI

Given a strongly stationary Markov chain and a finite set of stopping rules, we prove the existence of a polynomial algorithm which projects the Markov chain onto a minimal Markov chain without redundant information. Markov complexity is hence defined and tested on some classical problems.

Journal: :Complexity 2021

The Markov chain model teaching evaluation method is a quantitative analysis based on probability theory and stochastic process theory, which establishes mathematical to analyse the relationship in change development of real activities. Applying it achieve more comprehensive, reasonable, effective classroom quality college teachers positive significance for promoting continuous improvement leve...

Journal: :iranian journal of science and technology (sciences) 2006
r. meshkani

in a finite stationary markov chain, transition probabilities may depend on some explanatoryvariables. a similar problem has been considered here. the corresponding posteriors are derived andinferences are done using these posteriors. finally, the procedure is illustrated with a real example.

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