A new biased estimator based on ridge estimation

Abstract

Biased regression, Mean squared error, Multicollinearity, Ridge regression, Liu estimator,

Efficiency of a stochastic restricted two-parameter estimator in linear regression

“…Beside the two estimators, some other biased estimators as ones of remedies were put forward in the literature such as ridge-2 estimator [3], r À k class estimator [4][5], r À d class estimator [6], two-parameter estimator by Sakallıoglu and Kaçiranlar [7] and alternative two-parameter estimator by Özkale and Kaçiranlar [8].…”

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a b s t r a c t Sakallıoglu and Kaçiranlar (2008) proposed an estimator, two-parameter estimator, as an alternative to the ordinary least squares, the ordinary ridge and the Liu estimators in the presence of multicollinearity. In this paper, we introduce a new class estimator by combining the ideas underlying the mixed estimator and the two-parameter estimator when stochastic linear restrictions are assumed to hold.

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Generalized ridge estimation of a semiparametric regression model

“…Although there are many results about the ridge estimation of linear regression models [9][10][11] , to the best of our knowledge, nothing is known about one of a semiparametric regression model except Ref. [12].…”

Optimal Generalized Biased Estimator in Linear Regression Model

“…First we consider the data set on Portland cement originally due to [9]. This data set has since then been widely used by many researchers such as [10]- [13]. This data set came from an experimental investigation of the heat evolved during the setting and hardening of Portland cements of varied composition and the dependence of this heat on the percentages of four compounds in the clinkers from which the cement was produced.…”