Add to ORKGAbstract. In this paper, we study the nonparametric estimation of the regression function for dependent data with measurement errors in responses and covariates. The usual assumption in the errors-in-variables problem of indepedent errors can be replaced by dependent errors when the data are time series. Both cases are examined, and it is considered for first time the effect of measurement errors in responses when we are estimating nonparametrically the regression function
This paper considers identi\u85cation and estimation of a nonparametric regression model with an uno...
We show that difference-based methods can be used to construct simple and explicit estimators of err...
In this thesis we study the effect of regressors measured with an error on an estimated coefficients...
We consider the nonparametric estimation of the regression functions for dependentdata. Suppose that...
In this paper we estimate the nonparametric mean regression function when all the variables of the m...
The effect of errors in variables in nonparametric regression estimation is examined. To account for...
We propose a new nonparametric method for testing the parametric form of a regression function in th...
Covariates of regression analysis are often measured with error in medical research. Indeed, many me...
This paper provides a constructive argument for identification of nonparametric panel data models wi...
AbstractWe consider the problem of estimating a regression function with nonrandom design points and...
AbstractIn this paper we propose nonparametric estimates of the regression function and its derivati...
AbstractThe usual assumption in the classical errors-in-variables problem of independent measurement...
In this thesis we develop inferential methods for time series models with weakly dependent errors ...
In this paper, a partially linear multivariate model with error in the explanatory variable of the n...
Identi cation in errors-in-variables regression models was extended to wide models classes by S. Sch...
This paper considers identi\u85cation and estimation of a nonparametric regression model with an uno...
We show that difference-based methods can be used to construct simple and explicit estimators of err...
In this thesis we study the effect of regressors measured with an error on an estimated coefficients...
We consider the nonparametric estimation of the regression functions for dependentdata. Suppose that...
In this paper we estimate the nonparametric mean regression function when all the variables of the m...
The effect of errors in variables in nonparametric regression estimation is examined. To account for...
We propose a new nonparametric method for testing the parametric form of a regression function in th...
Covariates of regression analysis are often measured with error in medical research. Indeed, many me...
This paper provides a constructive argument for identification of nonparametric panel data models wi...
AbstractWe consider the problem of estimating a regression function with nonrandom design points and...
AbstractIn this paper we propose nonparametric estimates of the regression function and its derivati...
AbstractThe usual assumption in the classical errors-in-variables problem of independent measurement...
In this thesis we develop inferential methods for time series models with weakly dependent errors ...
In this paper, a partially linear multivariate model with error in the explanatory variable of the n...
Identi cation in errors-in-variables regression models was extended to wide models classes by S. Sch...
This paper considers identi\u85cation and estimation of a nonparametric regression model with an uno...
We show that difference-based methods can be used to construct simple and explicit estimators of err...
In this thesis we study the effect of regressors measured with an error on an estimated coefficients...