WOS: 000279486900012The paper introduces a new difference-based ridge regression estimator (beta) over cap (k) of the regression parameters beta in the partial linear model. Its mean-squared error is compared analytically with the non-ridge version (beta) over cap (0). Finally, the performance of the new estimator is evaluated for a real data set
Least square estimators in multiple linear regressions under multicollinearity become unstable as th...
During the past years, different kinds of estimators have been proposed as alternatives to the Ordin...
In this article, we introduce a ridge estimator for the vector of parameters in a semiparametric mod...
Differencing estimator, Differencing matrix, Multicollinearity, Ridge regression estimator, 62G08, 6...
In this paper, we consider a commonly used partially linear model. We proposed a restricted differen...
AbstractRidge regression estimator has been introduced as an alternative to the ordinary least squar...
AbstractConsidered the semiparametric regression model li=AiTX+s(ti)+Δi(i=1,2,…,n).Firstly, ridge es...
This article is concerned with the problem of multicollinearity in the linear part of a seemingly un...
Hoerl and Kennard (1970a) introduced the ridge regression estimator as an alternative to the ordinar...
AbstractHoerl and Kennard (1970a) introduced the ridge regression estimator as an alternative to the...
The ridge regression-type (Hoerl and Kennard, 1970) and Liu-type (Liu, 1993) estimators are consiste...
Ridge regression, a form of biased linear estimation, is a more appropriate technique than ordinary ...
AbstractThis paper proposes an adjusted ridge regression estimator for β for the linear regression m...
In this paper we introduce a new biased estimator for the vector of parameters in a linear regressio...
Multicollinearity is a major problem in linear regression analysis and several methods exists in the...
Least square estimators in multiple linear regressions under multicollinearity become unstable as th...
During the past years, different kinds of estimators have been proposed as alternatives to the Ordin...
In this article, we introduce a ridge estimator for the vector of parameters in a semiparametric mod...
Differencing estimator, Differencing matrix, Multicollinearity, Ridge regression estimator, 62G08, 6...
In this paper, we consider a commonly used partially linear model. We proposed a restricted differen...
AbstractRidge regression estimator has been introduced as an alternative to the ordinary least squar...
AbstractConsidered the semiparametric regression model li=AiTX+s(ti)+Δi(i=1,2,…,n).Firstly, ridge es...
This article is concerned with the problem of multicollinearity in the linear part of a seemingly un...
Hoerl and Kennard (1970a) introduced the ridge regression estimator as an alternative to the ordinar...
AbstractHoerl and Kennard (1970a) introduced the ridge regression estimator as an alternative to the...
The ridge regression-type (Hoerl and Kennard, 1970) and Liu-type (Liu, 1993) estimators are consiste...
Ridge regression, a form of biased linear estimation, is a more appropriate technique than ordinary ...
AbstractThis paper proposes an adjusted ridge regression estimator for β for the linear regression m...
In this paper we introduce a new biased estimator for the vector of parameters in a linear regressio...
Multicollinearity is a major problem in linear regression analysis and several methods exists in the...
Least square estimators in multiple linear regressions under multicollinearity become unstable as th...
During the past years, different kinds of estimators have been proposed as alternatives to the Ordin...
In this article, we introduce a ridge estimator for the vector of parameters in a semiparametric mod...