Results 241 to 250 of about 548,762 (295)

A note on general ridge estimator

Communications in Statistics - Theory and Methods, 1988
Necessary and sufficient conditions are obtained such that general ridge estimator of Hoerl and Kennard [4] supersedes the least squares estimator relative to the matrix mean square error.
exaly   +2 more sources

A new ridge estimator for linear regression model with some challenging behavior of error term

Communications in statistics. Simulation and computation, 2023
Ridge regression is a variant of linear regression that aims to circumvent the issue of collinearity among predictors. The ridge parameter k has an important role in the bias-variance tradeoff.
Maha Shabbir, S. Chand, F. Iqbal
semanticscholar   +1 more source

A robust counterpart approach for the ridge estimator to tackle outlier effect in restricted multicollinear regression models

Journal of Statistical Computation and Simulation, 2023
In statistics, regression analysis is a method for predicting a target variable by establishing the optimal linear relationship between the dependent and independent variables.
M. Roozbeh, M. Maanavi, N. A. Mohamed
semanticscholar   +1 more source

Restricted ridge estimator in the logistic regression model

Communications in Statistics Part B: Simulation and Computation, 2017
Yasin Asar, Mohammad Arashi, Jibo Wu
exaly   +2 more sources

Performance of ridge estimator in inverse Gaussian regression model

Communications in Statistics - Theory and Methods, 2019
Zakariya Yahya Algamal
exaly   +2 more sources

Ridge estimator in a mixed Poisson regression model

Communications in statistics. Simulation and computation, 2022
The generalized linear model approach of the mixed Poisson regression models (MPRM) is suitable for over-dispersed count data. The maximum likelihood estimator (MLE) is adopted to estimate their regression coefficients.
R. Tharshan, P. Wijekoon
semanticscholar   +1 more source

Poisson regression diagnostics with ridge estimation

Communications in Statistics - Simulation and Computation, 2021
Influential observations influence the Poisson regression model (PRM) inferences. There are the situations in the PRM, where the explanatory variables are correlated and influential observations oc...
Aamna Khan, Muhammad Aman Ullah, Muhammad Amin   +2 more
openaire   +1 more source

Modified ridge-type estimator for the zero inflated negative binomial regression model

Communications in statistics. Simulation and computation, 2023
The Zero-inflated negative binomial (ZINB) regression models are commonly used for count data that shows an over-dispersion and extra zeros. Multicollinearity is considered to be a significant issue in the estimation of parameters in the ZINB regression ...
M. Akram, Nimrah Afzal, Muhammad Amin, A. Batool   +3 more
semanticscholar   +1 more source

A non-asymptotic theory of Kernel Ridge Regression: deterministic equivalents, test error, and GCV estimator

arXiv.org
We consider learning an unknown target function $f_*$ using kernel ridge regression (KRR) given i.i.d. data $(u_i,y_i)$, $i\leq n$, where $u_i \in U$ is a covariate vector and $y_i = f_* (u_i) +\varepsilon_i \in \mathbb{R}$.
Theodor Misiakiewicz, B. Saeed
semanticscholar   +1 more source

A genetic algorithm for the estimation of ridges in fingerprints

IEEE Transactions on Image Processing, 1999
A genetic algorithm is developed to find the ridges in paper fingerprints. It is based on the fact that the ridges of the fingerprints are parallel. When scanning the fingerprint, line by line, the ideal noise-free gray level distribution should yield lines of black and white. The widths of these lines are not constant.
Ahmed S. Abutaleb, Mohamed S. Kamel
openaire   +2 more sources