Model Error in Covariance Structure Models

Restricted Likelihood Ratio Testing in Linear Mixed Models with General Error Covariance Structure

We consider the problem of testing for zero variance components in linear mixed models with correlated or heteroscedastic errors. In the case of independent and identically distributed errors, a valid test exists, which is based on the exact finite sample distribution of the restricted likelihood ratio test statistic under the null hypothesis. We propose to make use of a transformation to deriv...

Bayesian calibration of mathematical models: Optimization of model structure and examination of the role of process error covariance

Article history: Received 24 March 2013 Received in revised form 29 June 2013 Accepted 13 July 2013 Available online 19 July 2013

Symmetric Error Structure in Stochastic DEA

Estimating model error covariance matrix parameters in extended Kalman filtering

The extended Kalman filter (EKF) is a popular state estimation method for nonlinear dynamical models. The model error covariance matrix is often seen as a tuning parameter in EKF, which is often simply postulated by the user. In this paper, we study the filter likelihood technique for estimating the parameters of the model error covariance matrix. The approach is based on computing the likeliho...

Exploitation of particle filter for forecast error covariance structure estimation

The paper presents a scheme for estimation of spatio–temporal evolution of a quantity with unknown model error. Model error is estimated on basis of measured–minus– observed residuals evaluated upon measured and modeled values. Methods of Bayesian filtering are applied to the problem. The main contribution of this paper is application of general marginalized particle filter algorithm to the lin...