Abstract: We study the asymptotic behavior of M-estimates of regression parameters in multiple linear models where errors are dependent random variables. A Bahadur repre-sentation of the M-estimates is derived and a central limit theorem is established. The results are applied to linear models with errors being short-range dependent linear pro-cesses, heavy-tailed linear processes and some widely used nonlinear time series.
Summary. The paper is concerned with inference for linear models with fixed regressors and weakly de...
AbstractThe problem of simultaneous estimation of the regression parameters in a multiple regression...
AbstractWe propose a class of robust estimates for multivariate linear models. Based on the approach...
Abstract Consider the linear regression model yi=xiTβ+ei,i=1,2,…,n, $$y_{i}=x_{i}^{T}\beta+e_{i},\qu...
AbstractAsymptotics of M-estimators of the regression coefficients in linear models (both scale-vari...
This paper considers the asymptotic behavior of M -estimates in a dynamic linear regression model wh...
The limiting distribution of M-estimators of the regression parameter in linear models is derived un...
AbstractAsymptotics of M-estimators of the regression coefficients in linear models (both scale-vari...
AbstractAsymptotics of M-estimators of the regression coefficients in linear models (both scale-vari...
We consider asymptotic expansion of the nonparametric M-estimator in a fixed-design nonlinear regres...
International audienceIn this paper, we consider the usual linear regression model in the case where...
Consider the partly Linear model Y-i = X(i)'beta(0)+g(0)(T-i)+e(i), where {((Ti, X(i))}(infinit...
We construct a conservative error reporting function for the accuracy of M-estimators of a multi-dim...
International audienceIn this paper, we consider the usual linear regression model in the case where...
AbstractWe construct a conservative error reporting function for the accuracy of M-estimators of a m...
Summary. The paper is concerned with inference for linear models with fixed regressors and weakly de...
AbstractThe problem of simultaneous estimation of the regression parameters in a multiple regression...
AbstractWe propose a class of robust estimates for multivariate linear models. Based on the approach...
Abstract Consider the linear regression model yi=xiTβ+ei,i=1,2,…,n, $$y_{i}=x_{i}^{T}\beta+e_{i},\qu...
AbstractAsymptotics of M-estimators of the regression coefficients in linear models (both scale-vari...
This paper considers the asymptotic behavior of M -estimates in a dynamic linear regression model wh...
The limiting distribution of M-estimators of the regression parameter in linear models is derived un...
AbstractAsymptotics of M-estimators of the regression coefficients in linear models (both scale-vari...
AbstractAsymptotics of M-estimators of the regression coefficients in linear models (both scale-vari...
We consider asymptotic expansion of the nonparametric M-estimator in a fixed-design nonlinear regres...
International audienceIn this paper, we consider the usual linear regression model in the case where...
Consider the partly Linear model Y-i = X(i)'beta(0)+g(0)(T-i)+e(i), where {((Ti, X(i))}(infinit...
We construct a conservative error reporting function for the accuracy of M-estimators of a multi-dim...
International audienceIn this paper, we consider the usual linear regression model in the case where...
AbstractWe construct a conservative error reporting function for the accuracy of M-estimators of a m...
Summary. The paper is concerned with inference for linear models with fixed regressors and weakly de...
AbstractThe problem of simultaneous estimation of the regression parameters in a multiple regression...
AbstractWe propose a class of robust estimates for multivariate linear models. Based on the approach...
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