2017
DOI: 10.1007/s00362-017-0893-9
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Generalized difference-based weighted mixed almost unbiased ridge estimator in partially linear models

Abstract: In this paper, a generalized difference-based estimator is introduced for the vector parameter β in partially linear model when the errors are correlated. A generalized difference-based almost unbiased ridge estimator is defined for the vector parameter β. Under the linear stochastic constraint r = Rβ + e, a new generalized difference-based weighted mixed almost unbiased ridge estimator is proposed. The performance of this estimator over the generalized difference-based weighted mixed estimator, the generalize… Show more

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Cited by 32 publications
(15 citation statements)
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“…Also, some authors have developed two-parameter estimators to combat the problem of multicollinearity. e authors include Akdeniz and Kaçiranlar [7];Özkale and Kaçiranlar [8]; Sakallıoglu and Kaçıranlar [9]; Yang and Chang [10]; and very recently Roozbeh [11]; Akdeniz and Roozbeh [12]; and Lukman et al [13,14], among others. e objective of this paper is to propose a new oneparameter ridge-type estimator for the regression parameter when the predictor variables of the model are linear or nearto-linearly related.…”
Section: Introductionmentioning
confidence: 99%
“…Also, some authors have developed two-parameter estimators to combat the problem of multicollinearity. e authors include Akdeniz and Kaçiranlar [7];Özkale and Kaçiranlar [8]; Sakallıoglu and Kaçıranlar [9]; Yang and Chang [10]; and very recently Roozbeh [11]; Akdeniz and Roozbeh [12]; and Lukman et al [13,14], among others. e objective of this paper is to propose a new oneparameter ridge-type estimator for the regression parameter when the predictor variables of the model are linear or nearto-linearly related.…”
Section: Introductionmentioning
confidence: 99%
“…Hu [20] introduced a ridge estimator by the parametric component β. Liu et al [8] introduced a PCR estimator in partially linear models. For more references, one can refer to Roozbeh [21], Roozbeh et al [22], Akdeniz and Roozbeh [23], Roozbeh et al [24], Roozbeh and Hanzah [25], and Wei and Wang [26].…”
Section: Introductionmentioning
confidence: 99%
“…One of the mostly used regularization methods is the Tikhonov [21] regularization which was brought into statistical contexts by Hoerl and Kennard [12] as ridge regression. To mention a few recent researches, see e.g., [1,2,3,4,14,15,16].…”
Section: Introductionmentioning
confidence: 99%