In this paper, control variates are proposed to speed up Monte Carlo simulations to estimate expected error rates in multivariate classification.

This paper presents a Monte-Carlo study on the practical reliability of numerical algorithms for FIML-estimation in nonlinear econometric models. The performance of different techniques of Hessian approximation in trust-region algorithms is compared regarding their "robustness" against "bad"...

In the econometric literature simulation techniques are suggested for estimating standard errors of forecasts, especially in case of nonlinear models, where explicit analytic formulae are not available. For this purpose analytic simulation on coefficients, Monte Carlo on coefficients, Monte...