Bivariate linear mixed models using SAS proc MIXED.

By construction, the method MI-PLS proposed by Bastien (2008) will not take into account the random effect and then for assessing the contribution of our method we have

The focus of this research is to study the bias pattern in the naive estimator of a Lon- gitudinal Binary Mixed-effect model with Measurement error and Misclassification in

In both models with ME (with and without misclassification), when the variance of one measurement error increases, the bias of the naive estimator of the coefficient parameter of

First, the noise density was systematically assumed known and different estimators have been proposed: kernel estimators (e.g. Ste- fanski and Carroll [1990], Fan [1991]),

Our purpose is to derive the best linear unbiased estimator (BLUE) of the expected value of observations and the quadratic unbiased estimators (QUE) of the covariance

In this section, we adapt the results of Kappus and Mabon (2014) who proposed a completely data driven procedure in the framework of density estimation in deconvo- lution problems

Selection of fixed effects in high dimensional linear mixed models using a multicycle ECM algorithm.. Florian Rohart, Magali San Cristobal,

RAVIART, Mixed Finite Element Methods for Mh Order Elliptic Equations (to appear).. RAVIART, Interpolation Theory Over Curved Eléments, with Applications to Finite Element