Displaying similar documents to “On the solution of an integral equation of second type by the Monte-Carlo method”

Parallélisation d'une Combinaison des Méthodes de Monte-Carlo et Quasi-Monte-Carlo et Application aux Réseaux de Files d'Attente

Bruno Tuffin, Louis-Marie Le Ny (2010)

RAIRO - Operations Research

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We propose a parallel algorithm which uses both Monte-Carlo and quasi-Monte-Carlo methods. A detailed analysis of this algorithm, followed by examples, shows that the estimator's efficiency is a linear function of the processor number. As a concrete application example, we evaluate performance measures of a multi-class queueing network in steady state.

A Metropolis adjusted Nosé-Hoover thermostat

Benedict Leimkuhler, Sebastian Reich (2009)

ESAIM: Mathematical Modelling and Numerical Analysis

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We present a Monte Carlo technique for sampling from the canonical distribution in molecular dynamics. The method is built upon the Nosé-Hoover constant temperature formulation and the generalized hybrid Monte Carlo method. In contrast to standard hybrid Monte Carlo methods only the thermostat degree of freedom is stochastically resampled during a Monte Carlo step.

Valuation of large variable annuity portfolios: Monte Carlo simulation and synthetic datasets

Guojun Gan, Emiliano A. Valdez (2017)

Dependence Modeling

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Metamodeling techniques have recently been proposed to address the computational issues related to the valuation of large portfolios of variable annuity contracts. However, it is extremely diffcult, if not impossible, for researchers to obtain real datasets frominsurance companies in order to test their metamodeling techniques on such real datasets and publish the results in academic journals. To facilitate the development and dissemination of research related to the effcient valuation...

Quasi-Monte Carlo Methods for some Linear Algebra Problems. Convergence and Complexity

Karaivanova, Aneta (2010)

Serdica Journal of Computing

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We present quasi-Monte Carlo analogs of Monte Carlo methods for some linear algebra problems: solving systems of linear equations, computing extreme eigenvalues, and matrix inversion. Reformulating the problems as solving integral equations with a special kernels and domains permits us to analyze the quasi-Monte Carlo methods with bounds from numerical integration. Standard Monte Carlo methods for integration provide a convergence rate of O(N^(−1/2)) using N samples. Quasi-Monte Carlo methods...

Inference in linear models with inequality constrained parameters

Henning Knautz (2000)

Discussiones Mathematicae Probability and Statistics

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In many econometric applications there is prior information available for some or all parameters of the underlying model which can be formulated in form of inequality constraints. Procedures which incorporate this prior information promise to lead to improved inference. However careful application seems to be necessary. In this paper we will review some methods proposed in the literature. Among these there are inequality constrained least squares (ICLS), constrained maximum likelihood...

Local degeneracy of Markov chain Monte Carlo methods

Kengo Kamatani (2014)

ESAIM: Probability and Statistics

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We study asymptotic behavior of Markov chain Monte Carlo (MCMC) procedures. Sometimes the performances of MCMC procedures are poor and there are great importance for the study of such behavior. In this paper we call degeneracy for a particular type of poor performances. We show some equivalent conditions for degeneracy. As an application, we consider the cumulative probit model. It is well known that the natural data augmentation (DA) procedure does not work well for this model and the...

Numerical realization of the Bayesian inversion accelerated using surrogate models

Bérešová, Simona

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The Bayesian inversion is a natural approach to the solution of inverse problems based on uncertain observed data. The result of such an inverse problem is the posterior distribution of unknown parameters. This paper deals with the numerical realization of the Bayesian inversion focusing on problems governed by computationally expensive forward models such as numerical solutions of partial differential equations. Samples from the posterior distribution are generated using the Markov...

Estimating the shape parameter of the Topp-Leone distribution based on Type I censored samples

Husam Awni Bayoud (2015)

Applicationes Mathematicae

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The shape parameter of the Topp-Leone distribution is estimated from classical and Bayesian points of view based on Type I censored samples. The maximum likelihood and the approximate maximum likelihood estimates are derived. The Bayes estimate and the associated credible interval are approximated by using Lindley's approximation and Markov Chain Monte Carlo using the importance sampling technique. Monte Carlo simulations are performed to compare the performances of the proposed methods....

Numerical study of discretizations of multistage stochastic programs

Petri Hilli, Teemu Pennanen (2008)

Kybernetika

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This paper presents a numerical study of a deterministic discretization procedure for multistage stochastic programs where the underlying stochastic process has a continuous probability distribution. The discretization procedure is based on quasi-Monte Carlo techniques originally developed for numerical multivariate integration. The solutions of the discretized problems are evaluated by statistical bounds obtained from random sample average approximations and out-of-sample simulations....

Calibration and simulation of Heston model

Milan Mrázek, Jan Pospíšil (2017)

Open Mathematics

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We calibrate Heston stochastic volatility model to real market data using several optimization techniques. We compare both global and local optimizers for different weights showing remarkable differences even for data (DAX options) from two consecutive days. We provide a novel calibration procedure that incorporates the usage of approximation formula and outperforms significantly other existing calibration methods. We test and compare several simulation schemes using the parameters obtained...

Analysis on the individual efficiency prediction in the composed error frontier model. A Monte Carlo study.

Rafaela Dios Palomares, Antonio Ramos Millán, José Angel Roldán-Casas (2002)

Qüestiió

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This study seeks to analyse some important questions related to the Stochastic Frontier Model, such as the method proposed by Jondrow et al (1982) to separate the error term into its two components, and the measure of efficiency given by Timmer (1971). To this purpose, a Monte Carlo experiment has been carried out using the Half-Normal and Normal-Exponential specifications throughout the rank of the γ parameter. The estimation errors have been eliminated, so that the intrinsic variability...