In this paper Efficient Importance Sampling (EIS) is used to perform a classical and Bayesian analysis of univariate and multivariate Stochastic Volatility (SV) models for financial return series. EIS provides a highly generic and very accurate procedure for the Monte Carlo (MC) evaluation of high-dimensional interdependent integrals. It can be used to carry out ML-estimation of SV models as we...

In this work, we employ a Monte Carlo (MC) approach to investigate the temperature dependence of the electron transport in wurtzite InN. The velocity-field characteristics of this material show a pronounced negative differential resistance, which is a requirement for the realization of transferred-electron devices. Based on the Monte Carlo simulation results we derive a hydrodynamic mobility mo...

The electricity planning department of eThekwini Municipality performs a power system load forecast based on individual substation forecasts. The individual substation forecasts have uncertainty. It is desired to understand the effect of these uncertainties on the accuracy of the total system forecast. A Monte Carlo simulation of the forecasted system loadflow was performed. By means of this ap...

This paper proposes finite-sample procedures for testing the SURE specification in multi-equation regression models, i.e. whether the disturbances in different equations are contemporaneously uncorrelated or not. We apply the technique of Monte Carlo (MC) tests [Dwass (1957), Barnard (1963)] to obtain exact tests based on standard LR and LM zero correlation tests. We also suggest a MC quasi-LR ...

introduction : due to the importance of laser light penetration and propagation in biological tissues, many researchers have proposed several numerical methods such as monte carlo, finite element and green function methods. among them, the monte carlo method is an accurate method which can be applied for different tissues. however, because of its statistical nature, monte carlo simulation requi...

monte carlo methods designed base on stochastic reiterations and can be useful in uncertainty conditions. the purpose of this research was investigation of uncertainty to rank desertification indicators. in order to decrease uncertainty have been applied monte carlo reiterations for each value of indicator, if rank of xi is higher than rank of xk constantly. using multi dimension integrals the ...

We describe a tissue optics plug-in that interfaces with the GEANT4/GAMOS Monte Carlo (MC) architecture, providing a means of simulating radiation-induced light transport in biological media for the first time. Specifically, we focus on the simulation of light transport due to the Čerenkov effect (light emission from charged particle's traveling faster than the local speed of light in a given m...

A novel Monte Carlo (MC) approach is proposed for the simulation of wind speed samples to assess the wind energy production potential of a site. The Monte Carlo approach is based on historical wind speed data and reserves the effect of autocorrelation and seasonality in wind speed observations. No distributional assumptions are made, and this approach is relatively simple in comparison to simul...

In this paper, impacts of various uncertainties such as random outages of generating units and transmission lines, forecasting errors of load demand and wind power, in the presence of Demand response (DR) programs on power generation scheduling are studied. The problem is modelled in the form of a two-stage stochastic unit commitment (UC) which by solving it, the optimal solutions of UC as well...

in this paper, we calculate electron and hole impactionization coefficients in in0.52al0.48as using a monte carlo modelwhich has two valleys and two bands for electrons and holesrespectively. also, we calculate multiplication factor for electronand hole initiated multiplication regimes and breakdown voltagein in0.52al0.48as pin avalanche photodiodes. to validate themodel, we compare our simulat...