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Approximation of the marginal distributions of a semi-Markov process using a finite volume scheme

Christiane Cocozza-Thivent, Robert Eymard (2004)

ESAIM: Mathematical Modelling and Numerical Analysis - Modélisation Mathématique et Analyse Numérique

In the reliability theory, the availability of a component, characterized by non constant failure and repair rates, is obtained, at a given time, thanks to the computation of the marginal distributions of a semi-Markov process. These measures are shown to satisfy classical transport equations, the approximation of which can be done thanks to a finite volume method. Within a uniqueness result for the continuous solution, the convergence of the numerical scheme is then proven in the weak measure sense,...

Approximation of the marginal distributions of a semi-Markov process using a finite volume scheme

Christiane Cocozza-Thivent, Robert Eymard (2010)

ESAIM: Mathematical Modelling and Numerical Analysis

In the reliability theory, the availability of a component, characterized by non constant failure and repair rates, is obtained, at a given time, thanks to the computation of the marginal distributions of a semi-Markov process. These measures are shown to satisfy classical transport equations, the approximation of which can be done thanks to a finite volume method. Within a uniqueness result for the continuous solution, the convergence of the numerical scheme is then proven in the weak measure...

AR models with uniformly distributed noise

Michal Horváth (1989)

Aplikace matematiky

AR models are frequently used but usually with normally distributed white noise. In this paper AR model with uniformly distributed white noise are introduces. The maximum likelihood estimation of unknown parameters is treated, iterative method for the calculation of estimates is presented. A numerical example of this procedure and simulation results are also given.

Assessing influence in survival data with a cured fraction and covariates.

Edwin M. M. Ortega, Vicente G. Cancho, Victor Hugo Lachos (2008)

SORT

Diagnostic methods have been an important tool in regression analysis to detect anomalies, such as departures from error assumptions and the presence of outliers and influential observations with the fitted models. Assuming censored data, we considered a classical analysis and Bayesian analysis assuming no informative priors for the parameters of the model with a cure fraction. A Bayesian approach was considered by using Markov Chain Monte Carlo Methods with Metropolis-Hasting algorithms steps to...

Asymptotic behaviour of a BIPF algorithm with an improper target

Claudio Asci, Mauro Piccioni (2009)

Kybernetika

The BIPF algorithm is a Markovian algorithm with the purpose of simulating certain probability distributions supported by contingency tables belonging to hierarchical log-linear models. The updating steps of the algorithm depend only on the required expected marginal tables over the maximal terms of the hierarchical model. Usually these tables are marginals of a positive joint table, in which case it is well known that the algorithm is a blocking Gibbs Sampler. But the algorithm makes sense even...

Asymptotic unbiased density estimators

Nicolas W. Hengartner, Éric Matzner-Løber (2009)

ESAIM: Probability and Statistics

This paper introduces a computationally tractable density estimator that has the same asymptotic variance as the classical Nadaraya-Watson density estimator but whose asymptotic bias is zero. We achieve this result using a two stage estimator that applies a multiplicative bias correction to an oversmooth pilot estimator. Simulations show that our asymptotic results are available for samples as low as n = 50, where we see an improvement of as much as 20% over the traditionnal estimator.

Asymptotics of a Time-Splitting Scheme for the Random Schrödinger Equation with Long-Range Correlations

Christophe Gomez, Olivier Pinaud (2014)

ESAIM: Mathematical Modelling and Numerical Analysis - Modélisation Mathématique et Analyse Numérique

This work is concerned with the asymptotic analysis of a time-splitting scheme for the Schrödinger equation with a random potential having weak amplitude, fast oscillations in time and space, and long-range correlations. Such a problem arises for instance in the simulation of waves propagating in random media in the paraxial approximation. The high-frequency limit of the Schrödinger equation leads to different regimes depending on the distance of propagation, the oscillation pattern of the initial...

Automatic run-time choice for simulation length in mimesis

M. Becker, A.-L. Beylot, G. Damm, W.-Y. Thang (2010)

RAIRO - Operations Research

This paper presents an algorithm which prevents a simulation user from choosing a simulation length. This choice is always tricky and often leads to CPU-time waste, not to mention user-time waste. Too often, simulation users forget to compute confidence intervals: they only guess a simulation length and ignore the confidence on the simulation results. Those who do compute them generally try several lengths (and thus run several simulations) so as to obtain small enough confidence intervals. The...

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