Displaying similar documents to “Estimation with delayed observations”

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...

Γ-minimax sequential estimation for Markov-additive processes

Ryszard Magiera (2001)

Applicationes Mathematicae

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The problem of estimating unknown parameters of Markov-additive processes from data observed up to a random stopping time is considered. To the problem of estimation, the intermediate approach between the Bayes and the minimax principle is applied in which it is assumed that a vague prior information on the distribution of the unknown parameters is available. The loss in estimating is assumed to consist of the error of estimation (defined by a weighted squared loss function) as well...

The expected cumulative operational time for finite semi-Markov systems and estimation

Brahim Ouhbi, Ali Boudi, Mohamed Tkiouat (2007)

RAIRO - Operations Research

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In this paper we, firstly, present a recursive formula of the empirical estimator of the semi-Markov kernel. Then a non-parametric estimator of the expected cumulative operational time for semi-Markov systems is proposed. The asymptotic properties of this estimator, as the uniform strongly consistency and normality are given. As an illustration example, we give a numerical application.

Estimation of the transition density of a Markov chain

Mathieu Sart (2014)

Annales de l'I.H.P. Probabilités et statistiques

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We present two data-driven procedures to estimate the transition density of an homogeneous Markov chain. The first yields a piecewise constant estimator on a suitable random partition. By using an Hellinger-type loss, we establish non-asymptotic risk bounds for our estimator when the square root of the transition density belongs to possibly inhomogeneous Besov spaces with possibly small regularity index. Some simulations are also provided. The second procedure is of theoretical interest...

Explicit error bounds for Markov chain Monte Carlo

Daniel Rudolf

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We prove explicit, i.e. non-asymptotic, error bounds for Markov chain Monte Carlo methods. The problem is to compute the expectation of a function f with respect to a measure π. Different convergence properties of Markov chains imply different error bounds. For uniformly ergodic and reversible Markov chains we prove a lower and an upper error bound with respect to ||f||₂. If there exists an L₂-spectral gap, which is a weaker convergence property than uniform ergodicity, then we show...