AbstractFor the estimation of coefficients in a measurement error model, the least squares method utilizing original observations and averaged observations over replications provides inconsistent estimators. Based on these, consistent estimators are formulated and asymptotic properties are analyzed
A measurement error model is a regression model with (substantial) measurement errors in the variabl...
AbstractIn this paper we consider measurement error models when the observed random vectors are inde...
We consider the simple measurement error regression model y[subscript] t = [beta][subscript]0 + [bet...
For the estimation of coefficients in a measurement error model, the least squares method utilizing ...
AbstractFor the estimation of coefficients in a measurement error model, the least squares method ut...
AbstractA multivariate ultrastructural measurement error model is considered and it is assumed that ...
A multivariate ultrastructural measurement error model is considered and it is assumed that some pri...
AbstractThis paper examines the role of Stein estimation in a linear ultrastructural form of the mea...
AbstractA multivariate ultrastructural measurement error model is considered and it is assumed that ...
This paper considers consistent estimation of generalized linear models with covariate measurement e...
We propose a semiparametric estimator for varying coefficient models when the regressors in the nonp...
A measurement error model is a regression model with (substantial) measurement errors in the variabl...
We provide new tools for diagnosing and mitigating measurement error in list experiments. First, we...
A measurement error model is a regression model with (substantial) measurement errors in the variabl...
A measurement error model is a regression model with (substantial) measurement errors in the variabl...
A measurement error model is a regression model with (substantial) measurement errors in the variabl...
AbstractIn this paper we consider measurement error models when the observed random vectors are inde...
We consider the simple measurement error regression model y[subscript] t = [beta][subscript]0 + [bet...
For the estimation of coefficients in a measurement error model, the least squares method utilizing ...
AbstractFor the estimation of coefficients in a measurement error model, the least squares method ut...
AbstractA multivariate ultrastructural measurement error model is considered and it is assumed that ...
A multivariate ultrastructural measurement error model is considered and it is assumed that some pri...
AbstractThis paper examines the role of Stein estimation in a linear ultrastructural form of the mea...
AbstractA multivariate ultrastructural measurement error model is considered and it is assumed that ...
This paper considers consistent estimation of generalized linear models with covariate measurement e...
We propose a semiparametric estimator for varying coefficient models when the regressors in the nonp...
A measurement error model is a regression model with (substantial) measurement errors in the variabl...
We provide new tools for diagnosing and mitigating measurement error in list experiments. First, we...
A measurement error model is a regression model with (substantial) measurement errors in the variabl...
A measurement error model is a regression model with (substantial) measurement errors in the variabl...
A measurement error model is a regression model with (substantial) measurement errors in the variabl...
AbstractIn this paper we consider measurement error models when the observed random vectors are inde...
We consider the simple measurement error regression model y[subscript] t = [beta][subscript]0 + [bet...