This book presents an overview of the different errors-in-variables (EIV) methods that can be
used for system identification. Readers will explore the properties of an EIV problem. Such …

In this paper, we investigate the estimation and testing problems of partially linear varying-
coefficient errors-in-variables (EV) models under additional restricted condition. The …

In this paper, we apply empirical likelihood method to study the semi-parametric varying-
coefficient partially linear errors-in-variables models. Empirical log-likelihood ratio statistic …

In this paper we consider the problem of constructing non-asymptotic confidence regions for
the parameters of Errors-In-Variables (EIV) systems where both inputs and outputs are …

Generalized linear measurement error models, such as Gaussian regression, Poisson
regression and logistic regression, are considered. To eliminate the effects of measurement …

In this article, empirical likelihood inferences for the varying coefficient partially nonlinear
models are investigated. An empirical log-likelihood ratio function for the unknown …

The paper gives a survey of errors-in-variables methods in system identification.
Background and motivation are given, and examples illustrate why the identification problem …

This paper studies the partially time-varying coefficient models where some covariates are
measured with additive errors. In order to overcome the bias of the usual profile least …

This paper is concerned with statistical inference for partially nonlinear models. Empirical
likelihood method for parameter in nonlinear function and nonparametric function is …

We consider statistical inference for linear regression models when some variables are
distorted with errors by some unknown functions of commonly observable confounding …