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On some improved ridge estimators
Statistische Hefte, 1987zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Singh, Balvir, Chaubey, Yogendra P.
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Ridge Autoregression Estimation: LS Method
Communications in Statistics - Theory and Methods, 2015In an AR (p)-model, least-squares estimation of the parameters is considered when it is suspected that the parameters may belong to a linear subspace and the estimated covariance matrix is ill-conditioned. Accordingly, we define five estimators and study their properties in an asymptotic setup to discover dominance properties based on asymptotic ...
A. K. MD. Ehsanes Saleh, Amal F. Ghania
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1985
In this paper we introduce a new class of estimators, ridge type M-estimators, designed for analyzing linear regression models when regressor variables are multicollinear and residual distributions display long tails. The estimators are defined as weighted maximum likelihood type (M-) estimators when additional information about the parameters is given.
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In this paper we introduce a new class of estimators, ridge type M-estimators, designed for analyzing linear regression models when regressor variables are multicollinear and residual distributions display long tails. The estimators are defined as weighted maximum likelihood type (M-) estimators when additional information about the parameters is given.
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Communications in Statistics - Theory and Methods, 1998
Swindel (1976) introduced a modified ridge regression estimator based on prior information. Sarkar (1992) suggested a new estimator by combining in a particular way the two approaches followed in obtaining the restricted ieast squares and ordinary ndge regression estimators.
Kaçiranlar S. +2 more
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Swindel (1976) introduced a modified ridge regression estimator based on prior information. Sarkar (1992) suggested a new estimator by combining in a particular way the two approaches followed in obtaining the restricted ieast squares and ordinary ndge regression estimators.
Kaçiranlar S. +2 more
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A new biased estimator based on ridge estimation
Statistical Papers, 2006zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Sakallioglu S., Kaçiranlar S.
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Ridge regression. discussion and comparison of seven Ridge estimators
2013In the paper, the characteristics of seven different techniques of Ridge Regression are evaluated with respect to the same model. A consumption function with yearly data for Greece is therefore analysed and Monte-Carlo method s employed to check the performance of the estimation methods.
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Bayes minimax ridge regression estimators
Communications in Statistics - Theory and Methods, 2018ABSTRACTThe problem of estimating of the vector β of the linear regression model y = Aβ + ϵ with ϵ ∼ Np(0, σ2Ip) under quadratic loss function is considered when common variance σ2 is unknown.
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Characterization of general ridge estimators
Statistics & Probability Letters, 1996zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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BAYESIAN ESTIMATION OF T–G RIDGE MODEL
Statistica Neerlandica, 1984AbstractRidge type analysis of the Theil–Goldberger mixed model, considered earlier by Saxena and Bhatta–charya (1983) for the non–Bayesian set–up, is discussed from the Bayesian view–point when a has a closed prior and the loss–function being squared error.
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Structural basis of receptor recognition by SARS-CoV-2
Nature, 2020Jian Shang, Gang Ye, Ke Shi
exaly