We generalize the na\"ive estimator of a Poisson regression model with measurement errors as discussed in Kukush et al. [1]. The explanatory variable is not always normally distributed as they assume. In this study, we assume that the explanatory variable and measurement error are not limited to a normal distribution. We clarify the requirements for the existence of the na\"ive estimator and derive its asymptotic bias and asymptotic mean squared error (MSE). In addition, we propose a consistent estimator of the true parameter by correcting the bias of the na\"ive estimator. As illustrative examples, we present simulation studies that compare the performance of the na\"ive estimator and new estimator for a Gamma explanatory variable with a n...
This paper considers nonparametric instrumental variable regression when the endogenous variable is ...
Nonparametric prediction of a random variable Y conditional on the value of an explanatory variable ...
We consider the estimation of the regression of an outcome Y on a covariate X , where X is unob...
We consider two consistent estimators for the parameters of the linear predictor in the Poisson regr...
AbstractWe consider a Poisson model, where the mean depends on certain covariates in a log-linear wa...
We consider a regression of y on x given by a pair of mean and variance functions with a parameter v...
We consider a Poisson model, where the mean depends on certain covariates in a log-linear way with u...
A measurement error model is a regression model with (substantial) measurement errors in the variabl...
Graduation date: 1990This thesis considers the problem of estimating the linear\ud parameters of gen...
We present quasi-likelihood models for different regression problems when one of the explanatory var...
Poisson and negative binomial regression are widely used in analyzing count data or count data with ...
This article proposed the Modified Structural Quasi Score (MSQS) estimators for Poisson regression p...
I consider the estimation of linear regression models when the independent variables are measured wi...
This paper introduces a statistical method to estimate the parameters of bivariate structural errors...
AbstractIn this paper we consider measurement error models when the observed random vectors are inde...
This paper considers nonparametric instrumental variable regression when the endogenous variable is ...
Nonparametric prediction of a random variable Y conditional on the value of an explanatory variable ...
We consider the estimation of the regression of an outcome Y on a covariate X , where X is unob...
We consider two consistent estimators for the parameters of the linear predictor in the Poisson regr...
AbstractWe consider a Poisson model, where the mean depends on certain covariates in a log-linear wa...
We consider a regression of y on x given by a pair of mean and variance functions with a parameter v...
We consider a Poisson model, where the mean depends on certain covariates in a log-linear way with u...
A measurement error model is a regression model with (substantial) measurement errors in the variabl...
Graduation date: 1990This thesis considers the problem of estimating the linear\ud parameters of gen...
We present quasi-likelihood models for different regression problems when one of the explanatory var...
Poisson and negative binomial regression are widely used in analyzing count data or count data with ...
This article proposed the Modified Structural Quasi Score (MSQS) estimators for Poisson regression p...
I consider the estimation of linear regression models when the independent variables are measured wi...
This paper introduces a statistical method to estimate the parameters of bivariate structural errors...
AbstractIn this paper we consider measurement error models when the observed random vectors are inde...
This paper considers nonparametric instrumental variable regression when the endogenous variable is ...
Nonparametric prediction of a random variable Y conditional on the value of an explanatory variable ...
We consider the estimation of the regression of an outcome Y on a covariate X , where X is unob...