The consistency of MDL for linear regression models with increasing signal-to-noise ratio

IEEE Transactions on Signal Processing

Volumn 60, Issue 3, 2012, Pages 1508-1510

  Schmidt, Daniel F ^a   Makalic, Enes ^a  

^a UNIVERSITY OF MELBOURNE   (Australia)

Author keywords

Consistency; linear models; minimum description length; model selection

Indexed keywords

BAYESIAN INFORMATION CRITERION; BAYESIAN MIXTURE; CONSISTENCY; CONSISTENCY RESULT; LINEAR REGRESSION MODELS; MDL CRITERION; MINIMUM DESCRIPTION LENGTH; MINIMUM DESCRIPTION LENGTH PRINCIPLE; MODEL ORDER; MODEL SELECTION; NOISE VARIANCE; NORMALIZED MAXIMUM LIKELIHOOD; SIGNAL TO NOISE;

REGRESSION ANALYSIS;

INFORMATION THEORY;

EID: 84857216144     PISSN: 1053587X     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSP.2011.2177833     Document Type: Article

References (10)

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