Showing papers on "Particle filter published in 1989"
TL;DR: In this article, conditions under which the numerical approximation of a posterior moment converges almost surely to the true value as the number of Monte Carlo replications increases, and the numerical accuracy of this approximation may be assessed reliably, are set forth.
Abstract: Methods for the systematic application of Monte Carlo integration with importance sampling to Bayesian inference in econometric models are developed. Conditions under which the numerical approximation of a posterior moment converges almost surely to the true value as the number of Monte Carlo replications increases, and the numerical accuracy of this approximation may be assessed reliably, are set forth. Methods for the analytical verification of these conditions are discussed
1,649 citations
TL;DR: The basic vectorized algorithm along with description of several variations that have been developed by different researchers for specific applications are described, mainly in the areas of neutron transport in nuclear reactor and shielding analysis and photon transport in fusion plasmas.
9 citations
21 Aug 1989
TL;DR: This work relates the one to the other and characterize Monte-Carlo inference to exactly coincide with reliable frequency identification, on any set ℳ, and shows that reliable EX and BC-frequency inference forms a new discrete hierarchy.
Abstract: For EX and BC-type identification Monte-Carlo inference as well as reliable frequency identification on sets of functions are introduced. In particular, we relate the one to the other and characterize Monte-Carlo inference to exactly coincide with reliable frequency identification, on any set ℳ. Moreover, it is shown that reliable EX and BC-frequency inference forms a new discrete hierarchy having the breakpoints 1, 1/2, 1/3, ....
01 Oct 1989
TL;DR: The Monte Carlo method can be used to solve probabilistic potential problems in a fraction of the time required until now, and the concurrent methodology is powerful and is applicable to many other modelling techniques used for electromagnetic field modelling.
Abstract: This paper shows how the Monte Carlo method can be used to solve probabilistic potential problems in a fraction of the time required until now. Previous methods have relied on fast sequential processing using mainframe computers. The method presented here exploits the natural concurrency of the Monte Carlo approach. Computation is by a low cost transputer system linked to an PC-AT. The concurrent methodology is powerful and is applicable to many other modelling techniques used for electromagnetic field modelling. A microstrip geometry is considered since this exhibits most of the features required in a general problem. The considerations for designing the parallel algorithm are given. These considerations show the inherent strength of the concurrent approach and its flexibility in application to a broad class of passive electromagnetic field problems. The implications of adopting the concurrent methodologies suggested in this paper are of strategic importance in determining the direction in which passive microwave modelling should proceed in the future.