Model selection using modified AIC and BIC in joint modeling of paired functional data

Jiawei Wei and Lan Zhou

Statistics & Probability Letters, 2010, vol. 80, issue 23-24, 1918-1924

Abstract: A modified version of the Akaike information criterion and two modified versions of the Bayesian information criterion are proposed to select the number of principal components and to choose the penalty parameters of penalized splines in a joint model of paired functional data. Numerical results show that, compared with an existing procedure using the cross-validation, the procedure based on the information criteria is computationally much faster while giving a similar performance.

Keywords: AIC; BIC; Functional; principle; components; Penalized; splines; Mixed; effects; model (search for similar items in EconPapers)
Date: 2010
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