Maximum likelihood estimation for stochastic processes - a martingale approach

PII S0304 4076(98)00016 5 * Corresponding author E mail s j koopman@kub nl Journal of Econometrics 87 (1998) 271?301 Estimation of stochastic volatility models via Monte Carlo

Keywords: fractional Brownian motion, fractional Vasicek model, maximum likelihood estimation, strong consis- tency, asymptotic

Maximum likelihood estimation of a stochastic frontier model with residual covariance..

One aim of this paper is to modify and extend the classical work by Mikulevicius and Rozovskii [ 13 ] on weak or martingale solutions for SPDE in such a way so as to include

The theory is fascinating, and results in potentially super efficient estima- tors, the main intuition, in the context of CAR-censored data models, is that the covariates that enter

Further more detailed studies extended the results to stronger con- sistency and asymptotics under various assumption: such as in [9], authors discussed the asymptotics of the

The relative efficiency of the QML estimator when compared with estimators based on the General- ized Method of Moments is shown to be quite high for parameter values

The aim of this study is to evaluate the ef- fect of smoking on coronary heart disease (CHD) risk using Maximum Likelihood and Penalized Maximum Likelihood Estimation Methods