AbstractAsymptotics of M-estimators of the regression coefficients in linear models (both scale-variant and scale-invariant) when the number of regression coefficients tends to infinity as the sample size increases are investigated. The main purpose of this study is to establish the asymptotic properties under weaker conditions than those usually assumed, especially to relax the restrictions on the order of the dimension. Also, the conditions assumed and the results obtained seem easy to be extended to the multivariate linear models. In the second part of the paper, the asymptotic behavior of the scale-invariant M-estimates is considered
The effects of over- and underfitting the regression model is studied for M-estimators. Applying now...
In this paper, the constrained M-estimation of the regression coefficients and scatter parameters in...
In this paper, the constrained M-estimation of the regression coefficients and scatter parameters in...
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...
. In statistical analyses the complexity of a chosen model is often related to the size of available...
AbstractIn statistical analyses the complexity of a chosen model is often related to the size of ava...
In statistical analyses the complexity of a chosen model is often related to the size of available d...
Abstract We mainly study the M-estimation method for the high-dimensional linear regression model an...
Abstract: We study the asymptotic behavior of M-estimates of regression parameters in multiple linea...
AbstractIn statistical analyses the complexity of a chosen model is often related to the size of ava...
The limiting distribution of M-estimators of the regression parameter in linear models is derived un...
This thesis deals with asymptotic properties of least squares estimators of regression coefficients ...
summary:An asymptotic formula for the difference of the $M$-estimates of the regression coefficients...
When a statistic with a complicated distribution is dealt, the asymptotic distribution is often used...
The effects of over- and underfitting the regression model is studied for M-estimators. Applying now...
In this paper, the constrained M-estimation of the regression coefficients and scatter parameters in...
In this paper, the constrained M-estimation of the regression coefficients and scatter parameters in...
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...
. In statistical analyses the complexity of a chosen model is often related to the size of available...
AbstractIn statistical analyses the complexity of a chosen model is often related to the size of ava...
In statistical analyses the complexity of a chosen model is often related to the size of available d...
Abstract We mainly study the M-estimation method for the high-dimensional linear regression model an...
Abstract: We study the asymptotic behavior of M-estimates of regression parameters in multiple linea...
AbstractIn statistical analyses the complexity of a chosen model is often related to the size of ava...
The limiting distribution of M-estimators of the regression parameter in linear models is derived un...
This thesis deals with asymptotic properties of least squares estimators of regression coefficients ...
summary:An asymptotic formula for the difference of the $M$-estimates of the regression coefficients...
When a statistic with a complicated distribution is dealt, the asymptotic distribution is often used...
The effects of over- and underfitting the regression model is studied for M-estimators. Applying now...
In this paper, the constrained M-estimation of the regression coefficients and scatter parameters in...
In this paper, the constrained M-estimation of the regression coefficients and scatter parameters in...