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

Simulation estimators, such as indirect inference or simulated maximum likelihood, are successfully employed for estimating stochastic differential equations. They adjust for the bias (inconsistency) caused by discretization of the underlying stochastic process, which is in continuous time. The...

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

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

Simulation estimators, such as indirect inference or simulated maximum likelihood, are successfully employed for estimating stochastic differential equations. They adjust for the bias (inconsistency) caused by discretization of the underlying stochastic process, which is in continuous time. The...