Displaying similar documents to “Simple Monte Carlo integration with respect to Bernoulli convolutions”

Accelerated Monte Carlo estimation of exceedance probabilities under monotonicity constraints

Nicolas Bousquet (2012)

Annales de la faculté des sciences de Toulouse Mathématiques

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The problem of estimating the probability p = P ( g ( X ) 0 ) is considered when X represents a multivariate stochastic input of a monotonic function g . First, a heuristic method to bound p , originally proposed by de Rocquigny (2009), is formally described, involving a specialized design of numerical experiments. Then a statistical estimation of p is considered based on a sequential stochastic exploration of the input space. A maximum likelihood estimator of p build from successive dependent Bernoulli...

The chain records.

Gnedin, Alexander V. (2007)

Electronic Journal of Probability [electronic only]

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Central limit theorem for sampled sums of dependent random variables

Nadine Guillotin-Plantard, Clémentine Prieur (2010)

ESAIM: Probability and Statistics

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We prove a central limit theorem for linear triangular arrays under weak dependence conditions. Our result is then applied to dependent random variables sampled by a -valued transient random walk. This extends the results obtained by [N. Guillotin-Plantard and D. Schneider, (2003) 477–497]. An application to parametric estimation by random sampling is also provided.