Results 261 to 270 of about 24,864 (292)

Improved ridge regression estimators for the logistic regression model

Computational Statistics, 2013
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Saleh, A. K. Md. E., Kibria, B. M. Golam
openaire   +2 more sources

On ecological regression and ridge estimation

Communications in Statistics - Simulation and Computation, 1995
This paper focuses on the development of an ecological regression approach for voter transition estimation, avoiding the arbitrary assumptions in Goodman's classical model of ecological regression (Goodman [1959]). In doing this, we further develop previous attempts made at the ridge regression approach, by applying a modified generalized ridge ...
openaire   +1 more source

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.
openaire   +1 more source

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.
openaire   +1 more source

Condition Numbers and Minimax Ridge Regression Estimators

Journal of the American Statistical Association, 1985
Abstract Ridge regression was originally formulated with two goals in mind: improvement in mean squared error and numerical stability of the coefficient estimates. Conditions are given under which a minimax ridge regression estimator can also improve numerical stability, a quantity that can be measured with the condition number of the matrix to be ...
openaire   +1 more source

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
openaire   +1 more source

Performance of Some New Ridge Regression Estimators

Communications in Statistics - Simulation and Computation, 2003
In the ridge regression analysis, the estimation of ridge parameter k is an important problem. Many methods are available for estimating such a parameter. This article has considered some of these methods and also proposed some new estimators based on generalized ridge regression approach. A simulation study has been made to evaluate the performance of
openaire   +1 more source

On the almost unbiased ridge regression estimator

Communications in Statistics - Simulation and Computation, 1988
The purpose of this paper is two-fold. One is to compare the almost unbiased generalized ridge regression (AUGRR) estimator proposed by Singh, Chaubey and Dwivedi (1986) with the generalized ridge regression (GRR) estimator and with the ordinary least squares (OLS) estimator in terms of the mean squared error criterion.
openaire   +1 more source

Structural basis of receptor recognition by SARS-CoV-2

Nature, 2020
Jian Shang, Gang Ye, Ke Shi
exaly  

Heteroscedasticity consistent ridge regression estimators in linear regression model

Communications in Statistics - Simulation and Computation, 2023
Irum Sajjad Dar, Sohail Chand
openaire   +1 more source