Restricted estimation in multivariate measurement error regression model

Restricted regression estimation in measurement error models

The problem of consistent estimation of the regression coefficients when some prior information about the regression coefficients is available is considered. Such prior information is expressed in the form of exact linear restrictions. The knowledge of covariance matrix of measurement errors that is associated with explanatory variables is used to construct the consistent estimators. Some consi...

Estimation of Regression Coefficients in a Restricted Measurement Error Model Using Instrumental Variables

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Ridge Stochastic Restricted Estimators in Semiparametric Linear Measurement Error Models

In this article we consider the stochastic restricted ridge estimation in semipara-metric linear models when the covariates are measured with additive errors. The development of penalized corrected likelihood method in such model is the basis for derivation of ridge estimates. The asymptotic normality of the resulting estimates are established. Also, necessary and sufficient condition...

Corrigendum to "Ridge regression estimation approach to measurement error model" [J. Multivariate Analysis 123 (2014) 68-84]

Estimation in autoregressive model with measurement error

Consider an autoregressive model with measurement error: we observe Zi = Xi + εi, where Xi is a stationary solution of the autoregressive equation Xi = fθ0(Xi−1) + ξi. The regression function fθ0 is known up to a finite dimensional parameter θ. The distributions of X0 and ξ1 are unknown whereas the distribution of ε0 is completely known. We want to estimate the parameter θ by using the observat...