Results 261 to 270 of about 25,104 (288)

Minimax Linear Regression Estimators With Application to Ridge Regression

Technometrics, 1982
This article considers minimax linear estimation of β in the multiple linear-regression model Y = Xβ + ξ. Some results from European publications are referenced and summarized and some new results are given. These minimax estimators of β can also be classified as ridgeregression estimators with nonstochastic ridge parameters.
Lawrence Peele, Thomas P. Ryan
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ROBUST RIDGE REGRESSION BASED ON AN M‐ESTIMATOR

Australian Journal of Statistics, 1991
SummaryConsider the linear regression model y=β01 +Xβ+ in the usual notation. It is argued that the class of ordinary ridge estimators obtained by shrinking the least squares estimator by the matrix (X1X + kI)‐1X'X is sensitive to outliers in the ^variable.
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Inequality constrained ridge regression estimator

Statistics & Probability Letters, 2013
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Toker S., Üstündag Şiray G., Kaçiranlar S.   +2 more
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Ridge Regression Estimation for Survey Samples

Communications in Statistics - Theory and Methods, 2008
This paper describes procedure for constructing a vector of regression weights. Under the regression superpopulation model, the ridge regression estimator that has minimum model mean squared error is derived. Through a simulation study, we compare the ridge regression weights, regression weights, quadratic programming weights, and raking ratio weights.
Mingue Park, Min Yang
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More on the unbiased ridge regression estimation

Statistical Papers, 2014
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Wu, Jibo, Yang, Hu
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Ridge estimator in a mixed Poisson regression model

Communications in Statistics - Simulation and Computation, 2022
Ramajeyam Tharshan, Pushpakanthie Wijekoon   +1 more
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A mixed estimator interpretation of ridge regression

Social Science Research, 1982
Abstract It is shown that a formal isomorphism between the ridge estimator and the homogeneous case of the Theil-Goldberger mixed estimator leads to a general interpretation of ridge regression as ordinary least squares estimation subject to a prior stochastic constraint that all slope coefficients in the model are zero. Users of ridge regression are
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Ridge regression. discussion and comparison of seven Ridge estimators

2013
In 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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Heteroscedasticity consistent ridge regression estimators in linear regression model

Communications in Statistics - Simulation and Computation, 2023
Irum Sajjad Dar, Sohail Chand
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Quantile-based robust ridge m-estimator for linear regression model in presence of multicollinearity and outliers

Communications in Statistics Part B: Simulation and Computation, 2021
Muhammad Suhail, Sohail Chand, B M Golam Kibria   +2 more
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