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

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. 2010 Elsevier B.V.

authors

• Zhou, Lan

published proceedings

• STATISTICS & PROBABILITY LETTERS

author list (cited authors)

• Wei, J., & Zhou, L.

citation count

• 9

complete list of authors

• Wei, Jiawei||Zhou, Lan

publication date

• December 2010

publisher

• Elsevier  Publisher

published in

• Statistics and Probability Letters  Journal

keywords

• Aic
• Functional Principle Components
• Mixed Effects Model
• Penalized Splines
• Sic

Digital Object Identifier (DOI)

• 10.1016/j.spl.2010.08.020

start page

• 1918

end page

• 1924

volume

• 80

issue

• 23-24

URL

• http://dx.doi.org/10.1016/j.spl.2010.08.020