Simplex regression models with measurement error
Jalmar M. F. Carrasco, Nancy M. Reid · Communications in Statistics - Simulation and Computation · 2019
This paper considers the simplex regression model when there is measurement error in the covariate. We consider a structural approach where the measurement error follows a normal or gamma distribution. We apply a Monte Carlo EM algorithm to estimate the parameters using a pseudo-likelihood function. A simulation study is used to investigate the impact of ignoring the measurement error. Finally, the results are illustrated with a data set.