Results 271 to 280 of about 7,690 (301)

A volumetric approach to biased estimation: Demonstration on shrinkage estimators

2016 IEEE International Conference on Digital Signal Processing (DSP), 2016
This work proposes a new approach, named as the volumetric design (VD), of developing biased estimators of deterministic parameters that are known in advance to belong to a compact subset in the parameter space. For analytical tractability, this approach is demonstrated on the choice of the shrinkage parameter of an estimator that scales the celebrated
Bikcora, C., Weiland, S.
openaire   +2 more sources

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
openaire   +2 more sources

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
openaire   +1 more source

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
openaire   +1 more source

Shrinkage averaging estimation

Statistical Papers, 2011
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +2 more sources

Partial Kelly portfolios and shrinkage estimators

2012 IEEE International Symposium on Information Theory Proceedings, 2012
The log-optimal or Kelly portfolio forms the basis of a theoretically appealing investment strategy. However, it is difficult to compute, and this hinders its adoption in practice. In this paper we consider an approximate Kelly portfolio based on maximizing the expected value of a quadratic approximation to log utility.
Justin K. Rising, Abraham J. Wyner
openaire   +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
openaire   +1 more source

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
openaire   +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 ...
openaire   +1 more source

SHRINKAGE ESTIMATION FOR NEARLY SINGULAR DESIGNS

Econometric Theory, 2007
Summary: Shrinkage estimation procedures such as ridge regression and the lasso have been proposed for stabilizing estimation in linear models when high collinearity exists in the design. In this paper, we consider asymptotic properties of shrinkage estimators in the case of ``nearly singular'' designs.
openaire   +2 more sources