Results 41 to 50 of about 24,864 (292)

Estimation in high-dimensional linear models with deterministic design matrices [PDF]

open access: yes, 2012
Because of the advance in technologies, modern statistical studies often encounter linear models with the number of explanatory variables much larger than the sample size.
Deng, Xinwei, Shao, Jun
core   +1 more source

Feasible Generalized Stein-Rule Restricted Ridge Regression Estimators [PDF]

open access: yesJournal of Applied Mathematics, Statistics and Informatics, 2017
AbstractSeveral versions of the Stein-rule estimators of the coefficient vector in a linear regression model are proposed in the literature. In the present paper, we propose new feasible generalized Stein-rule restricted ridge regression estimators to examine multicollinearity and autocorrelation problems simultaneously for the general linear ...
Ozbay, N., Dawoud, I., Kaciranlar, S.
openaire   +3 more sources

Performance of some estimators for the multicollinear logistic regression model: theory, simulation, and applications

open access: yesResearch in Statistics
This article proposes some new estimators, namely Stein’s estimators for ridge regression and Kibria and Lukman estimator and compares their performance with some existing estimators, namely maximum likelihood estimator (MLE), ridge regression estimator,
Md Ariful Hoque, B. M. Golam Kibria
doaj   +1 more source

Biased proportional hazard regression estimator in the existence of collinearity

open access: yesHeliyon, 2023
This paper proposed a new biased proportional hazard regression (PHR) estimator which is the combination of elastic net proportional hazard regression (ENPHR) and principal components proportional hazard regression (PCPHR) estimator.
Anu Sirohi   +3 more
doaj   +1 more source

Bayesian Estimation Improves Prediction of Outcomes After Epilepsy Surgery

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT We estimated the statistical power of studies predicting seizure freedom after epilepsy surgery. We extracted data from a Cochrane meta‐analysis. The median power across all studies was 14%. Studies with a median sample size or less (n ≤ 56) and a statistically significant result exaggerated the true effect size by a factor of 5.4, while the ...
Adam S. Dickey   +4 more
wiley   +1 more source

Hopfield Neural Networks for Online Constrained Parameter Estimation With Time‐Varying Dynamics and Disturbances

open access: yesInternational Journal of Adaptive Control and Signal Processing, EarlyView.
This paper proposes two projector‐based Hopfield neural network (HNN) estimators for online, constrained parameter estimation under time‐varying data, additive disturbances, and slowly drifting physical parameters. The first is a constraint‐aware HNN that enforces linear equalities and inequalities (via slack neurons) and continuously tracks the ...
Miguel Pedro Silva
wiley   +1 more source

Modified Liu estimator to address the multicollinearity problem in regression models: A new biased estimation class

open access: yesScientific African, 2022
The multicollinearity problem occurrence of the explanatory variables affects the least-squares (LS) estimator seriously in the regression models. The multicollinearity adverse effects on the LS estimation are also investigated by lots of authors.
Issam Dawoud   +2 more
doaj   +1 more source

Enhancing Corrosion Resistance and Mechanical Strength of 3D‐Printed Iron Polylactic Acid for Marine Applications via Laser Surface Texturing

open access: yesAdvanced Engineering Materials, EarlyView.
Laser surface texturing significantly improves the corrosion resistance and mechanical strength of 3D‐printed iron polylactic acid (Ir‐PLA) for marine applications. Optimal laser parameters reduce corrosion by 80% and enhance tensile strength by 25% and ductility by 15%.
Mohammad Rezayat   +6 more
wiley   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

open access: yesAdvanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt   +8 more
wiley   +1 more source

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