Optimality of the quasi-score estimator in a mean–variance model with applications to measurement error models

Optimality of the quasi-score estimator in a mean-variance model with applications to measurement error models

A New Ridge Estimator in Linear Measurement Error Model with Stochastic Linear Restrictions

In this paper, we propose a new ridge-type estimator called the new mixed ridge estimator (NMRE) by unifying the sample and prior information in linear measurement error model with additional stochastic linear restrictions. The new estimator is a generalization of the mixed estimator (ME) and ridge estimator (RE). The performances of this new estimator and mixed ridge estimator (MRE) against th...

Asymptotic optimality of the quasi-score estimator in a class of linear score estimators

We prove that the quasi-score estimator in a mean-variance model is optimal in the class of (unbiased) linear score estimators, in the sense that the difference of the asymptotic covariance matrices of the linear score and quasi-score estimator is positive semi-definite. We also give conditions under which this difference is zero or under which it is positive definite. This result can be applie...

Bias of the Quasi Score Estimator of a Measurement Error Model Under Misspecification of the Regressor Distribution

In a structural error model the structural quasi score (SQS) estimator is based on the distribution of the latent regressor variable. If this distribution is misspecified the SQS estimator is (asymptotically) biased. Two types of misspecification are considered. Both assume that the statistician erroneously adopts a normal distribution as his model for the regressor distribution. In the first t...

Quasi Score is more efficient than Corrected Score in a general nonlinear measurement error model

We compare two consistent estimators of the parameter vector β of a general exponential family measurement error model with respect to their relative efficiency. The quasi score (QS) estimator uses the distribution of the regressor, the corrected score (CS) estimator does not make use of this distribution and is therefore more robust. However, if the regressor distribution is known, QS is asymp...