Displaying similar documents to “Parameter estimation in stochastic systems: some recent results and applications”

An estimation method for the reliability of "consecutive-k-out-of-n system"

Ksir, Brahim (2012)

Serdica Mathematical Journal

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2010 Mathematics Subject Classification: 60K10, 60K20, 60J10, 60J20, 62G02, 62G05, 68M15, 62N05, 68M15. This paper is concerned with consecutive-k-out-of-n system in which all the components have the same q lifetime probability, so, it's possible to estimate q from a sample by using the maximum likelihood principle. In the reliability formula of the consecutive-k-out-of-n system appears the term q^k. The goal in this work is to propose a direct estimation of q^k to avoid...

Likelihood for interval-censored observations from multi-state models.

Daniel Commenges (2003)

SORT

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We consider the mixed dicrete-continuous pattern of observation in a multi-state model; this is a classical pattern because very often clinical status is assessed at discrete visit times while time of death is observed exactly. The likelihood can easily be written heuristically for such models. However a formal proof is not easy in such observational patterns. We give a rigorous derivation al the likelihood for the illness-death model based on applying Jacod´s formula to an observed...

Approximate maximum likelihood estimation for a spatial point pattern.

Jorge Mateu, Francisco Montes (2000)

Qüestiió

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Several authors have proposed stochastic and non-stochastic approximations to the maximum likelihood estimate for a spatial point pattern. This approximation is necessary because of the difficulty of evaluating the normalizing constant. However, it appears to be neither a general theory which provides grounds for preferring a particular method, nor any extensive empirical comparisons. In this paper, we review five general methods based on approximations to the maximum likelihood estimate...

Estimation of hidden Markov models for a partially observed risk sensitive control problem

Bernard Frankpitt, John S. Baras (1998)

Kybernetika

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This paper provides a summary of our recent work on the problem of combined estimation and control of systems described by finite state, hidden Markov models. We establish the stochastic framework for the problem, formulate a separated control policy with risk-sensitive cost functional, describe an estimation scheme for the parameters of the hidden Markov model that describes the plant, and finally indicate how the combined estimation and control problem can be re-formulated in a framework...

Fast simulation for Road Traffic Network

Roberta Jungblut-Hessel, Brigitte Plateau, William J. Stewart, Bernard Ycart (2010)

RAIRO - Operations Research

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In this paper we present a method to perform fast simulation of large Markovian systems. This method is based on the use of three concepts: Markov chain uniformization, event-driven dynamics, and modularity. An application of urban traffic simulation is presented to illustrate the performance of our approach.

Stochastic differential equation driven by a pure-birth process

Marta Tyran-Kamińska (2002)

Annales Polonici Mathematici

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A generalization of the Poisson driven stochastic differential equation is considered. A sufficient condition for asymptotic stability of a discrete time-nonhomogeneous Markov process is proved.

On the Bayesian estimation for the stationary Neyman-Scott point processes

Jiří Kopecký, Tomáš Mrkvička (2016)

Applications of Mathematics

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The pure and modified Bayesian methods are applied to the estimation of parameters of the Neyman-Scott point process. Their performance is compared to the fast, simulation-free methods via extensive simulation study. Our modified Bayesian method is found to be on average 2.8 times more accurate than the fast methods in the relative mean square errors of the point estimates, where the average is taken over all studied cases. The pure Bayesian method is found to be approximately as good...

Systems of differential equations modeling non-Markov processes

Irada Dzhalladova, Miroslava Růžičková (2023)

Archivum Mathematicum

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The work deals with non-Markov processes and the construction of systems of differential equations with delay that describe the probability vectors of such processes. The generating stochastic operator and properties of stochastic operators are used to construct systems that define non-Markov processes.