Estimation of Nonlinear Errors-in-Variables Models

Identification of nonlinear errors-in-variables models

The paper is about a generalization of a classical eigenvalue-decomposition method originally developed for errors–in-variables linear system identification to handle an important class of nonlinear problems. A number of examples are presented to call the attention to the most critical part of the procedure turning the identification problem to a generalized eigenvalue-eigenvector calculation p...

Efficient Estimation of Errors-in-Variables Models

The paper addresses the discrete-time linear process identification problem assuming noisy input and output records available for the parameter estimation. The efficient algorithms are derived for the simultaneous estimation of the process and noise parameters. Implementation techniques based on matrix and polynomial decompositions are given in details resulting in estimation algorithms with re...

Nonlinear Errors in Variables: Estimation of Some Engel Curves

Method of Moments Estimation and Identifiability of Semiparametric Nonlinear Errors-in-Variables Models

This paper deals with a nonlinear errors-in-variables model where the distributions of the unobserved predictor variables and of the measurement errors are nonparametric. Using the instrumental variable approach, we propose method of moments estimators for the unknown parameters and simulation-based estimators to overcome the possible computational difficulty of minimizing an objective function...

Estimation of Censored Linear Errors-in-Variables Models∗

This paper deals with a linear errors-in-variables model where the dependent variable is censored. A two-step procedure is proposed to derive the moment estimator of the model and the corresponding asymptotic covariance matrix. The results cover the moment estimation of the usual (error-free) Tobit model as a special case. It is shown that, under normality and a certain identifying condition, t...