Group coordinate descent algorithms for nonconvex penalized regression

Computational Statistics and Data Analysis

Volumn 56, Issue 2, 2012, Pages 316-326

  Wei, Fengrong ^a   Zhu, Hongxiao ^b  

^a UNIVERSITY OF WEST GEORGIA   (United States)

^b Statistical and Applied Mathematical Sciences Institute USA   (United States)

Author keywords

Group coordinate decent algorithm; Grouping structure; High dimension; Minimax concave penalty; Smoothly clipped absolute deviation penalty

Indexed keywords

COMPUTATION BURDEN; COORDINATE DESCENT; COVARIATES; DATA EXAMPLES; ESTIMATED PARAMETER; GCD ALGORITHM; GLOBAL MINIMA; GROUP COORDINATES; GROUP SELECTION; HIGH DIMENSIONS; LINEAR REGRESSION MODELS; LOCAL MINIMUMS; LOGISTIC REGRESSIONS; MINIMAX; MODEL FITTING METHOD; NONCONVEX; NONCONVEXITY; OBJECTIVE FUNCTIONS; PARAMETER SPACES; PENALIZED LIKELIHOOD; PENALTY FUNCTION; SAMPLE SIZES; SIMULATION STUDIES; SMOOTHLY CLIPPED ABSOLUTE DEVIATION; VARIABLE SELECTION;

ALGORITHMS; ECHO SUPPRESSION; LINEAR REGRESSION;

COMPUTATIONAL EFFICIENCY;

EID: 80053280974     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.csda.2011.08.007     Document Type: Article

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