Smooth Blockwise Iterative Thresholding: A Smooth Fixed Point Estimator Based on the Likelihood’s Block Gradient

The proposed smooth blockwise iterative thresholding estimator (SBITE) is a model selection technique defined as a fixed point reached by iterating a likelihood gradient-based thresholding function. The smooth James-Stein thresholding function has two regularization parameters λ and ν, and a smoothn...

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Bibliographic Details
Published in:	Journal of the American Statistical Association Vol. 107; no. 498; pp. 800 - 813
Main Author:	Sardy, Sylvain
Format:	Journal Article
Language:	English
Published:	Alexandria Taylor & Francis Group 01.06.2012 Taylor & Francis Ltd
Subjects:	Adaptive lasso Analytical estimating Bias Estimation Estimation methods Estimators Function Grammatical aspect Gravitational waves Inequality Information criterion Iterative block thresholding James-Stein estimator Mathematical independent variables Modeling Monte Carlo method Monte Carlo methods Monte Carlo simulation Motivation Multivariate analysis Multivariate time series Oracles Property Regression analysis Risk risk estimate Simulation Sparse model selection Statistics Theory and Methods Threshing Time series time series analysis Time series models Unbiased estimators Universal threshold Wavelet smoothing
ISSN:	1537-274X, 0162-1459, 1537-274X
Online Access:	Get full text
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