This paper considers linear regression models when neither the response variable nor the
covariates can be directly observed, but are measured with multiplicative distortion …

We consider modal linear regression models when neither the response variable nor the
covariates can be directly observed, but are measured with multiplicative distortion …

This paper considers nonlinear regression models when neither the response variable nor
the covariates can be directly observed, but are measured with both multiplicative and …

This paper considers partial linear single-index regression models when all the variables
are measured with multiplicative distortion measurement errors. To eliminate the effect …

In this article, we propose a new identifiability condition by using the logarithmic calibration
for the distortion measurement error models, where neither the response variable nor the …

This paper considers partial linear regression models when neither the response variable
nor the covariates can be directly observed, but are instead measured with both …

In this paper we consider partial linear regression models when all the variables are
measured with multiplicative distortion measurement errors. To eliminate the effect caused …

This research provides a projection-based test to check parametric single-index regression
structure in variable-adjusted models. An adaptive-to-model strategy is employed, which …

This paper studies the estimation of correlation coefficient between unobserved variables of
interest. These unobservable variables are distorted in a multiplicative fashion by an …

A logarithmic calibration estimation procedure is proposed for nonparametric regression
models under the multiplicative distortion measurement errors setting. The unobservable …