Results 291 to 300 of about 479,757 (331)

ON SHRINKAGE TOWARDS AN ARBITRARY ESTIMATOR

Statistics & Risk Modeling, 1991
For estimating the unknown mean \(\theta \in R^ p\) of a multinormal distribution with independent components and common variance \(\sigma^ 2\) several minimax estimators with respect to quadratic loss are known. The author considers a class of spherically symmetric estimators. These are an adaptive linear combination of the identity estimator X and of
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On the shrinkage of local linear curve estimators

Statistics and Computing, 1997
Local linear curve estimators are typically constructed using a compactly supported kernel, which minimizes edge effects and (in the case of the Epanechnikov kernel) optimizes asymptotic performance in a mean square sense. The use of compactly supported kernels can produce numerical problems, however.
Cheng, Ming-Yen, Hall, Peter, Titterington, D.M.   +2 more
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Shrinkage Ridge Estimators in Linear Regression

Communications in Statistics - Simulation and Computation, 2013
The problem of estimation of the regression coefficients in a multiple regression model (MRM) is considered under multicollinearity situation. Further it is suspected that the regression coefficients may be restricted to a subspace. In this approach, we present the estimators of the regression coefficients combining the idea of preliminary test ...
Mohammad Arashi, S. M. M. Tabatabaey, M. Hassanzadeh Bashtian   +2 more
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Shrinkage averaging estimation

Statistical Papers, 2011
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Pretest and shrinkage estimators for log-normal means

Computational statistics (Zeitschrift), 2022
Mahmoud Aldeni, John C. Wagaman, M. Amezziane, S. Ahmed   +3 more
semanticscholar   +1 more source

Shrinkage estimation in general linear models

Computational Statistics & Data Analysis, 2009
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Lihua An, Sévérien Nkurunziza, Karen Y. Fung, Daniel Krewski, Isaac Luginaah   +4 more
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An Efficient SVD Shrinkage for Rank Estimation

IEEE Signal Processing Letters, 2015
Matrix rank estimation is a classical problem with many applications in statistical signal processing. In this letter, a logistic function based thresholding of the singular values is proposed for the rank estimation purpose. Parameters of the proposed shrinkage function are tuned using Stein’s unbiased risk estimator.
Santosh Kumar Yadav, Rohit Sinha 0003, Prabin Kumar Bora   +2 more
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Shrinking the Variance: Shrinkage Baselines for Reinforcement Learning with Verifiable Rewards

arXiv.org
Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a powerful paradigm for post-training large reasoning models (LRMs) using policy-gradient methods such as GRPO.
Guanning Zeng, Zhaoyi Zhou, Daman Arora, Andrea Zanette   +3 more
semanticscholar   +1 more source

Improved Shrinkage Estimation of Relative Potency

Biometrical Journal, 1995
AbstractThis article considers the asymptotic estimation theory for the log relative potency in a symmetric parallel bioassay when uncertain prior information about the true log relative potency is assumed to be a known quantity. Three classes of point estimation, namely, the unrestricted estimator, the shrinkage restricted estimator and shrinkage ...
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A comparative study of the performance of new ridge estimators for multicollinearity: Insights from simulation and real data application

AIP Advances
This paper addresses the challenge of multicollinearity in regression models, a condition that inflates the standard errors of coefficients, leading to unreliable estimates and wider confidence intervals.
Nadeem Akhtar, M. Alharthi
semanticscholar   +1 more source