Functional data analysis in an operator-based mixed-model framework

TY - JOUR

T1 - Functional data analysis in an operator-based mixed-model framework

AU - Markussen, Bo

PY - 2013/2/1

Y1 - 2013/2/1

N2 - Functional data analysis in a mixed-effects model framework is done using operator calculus. In this approach the functional parameters are treated as serially correlated effects giving an alternative to the penalized likelihood approach, where the functional parameters are treated as fixed effects. Operator approximations for the necessary matrix computations are proposed, and semi-explicit and numerically stable formulae of linear computational complexity are derived for likelihood analysis. The operator approach renders the usage of a functional basis unnecessary and clarifies the role of the boundary conditions.

AB - Functional data analysis in a mixed-effects model framework is done using operator calculus. In this approach the functional parameters are treated as serially correlated effects giving an alternative to the penalized likelihood approach, where the functional parameters are treated as fixed effects. Operator approximations for the necessary matrix computations are proposed, and semi-explicit and numerically stable formulae of linear computational complexity are derived for likelihood analysis. The operator approach renders the usage of a functional basis unnecessary and clarifies the role of the boundary conditions.

U2 - 10.3150/11-BEJ389

DO - 10.3150/11-BEJ389

M3 - Journal article

SN - 1350-7265

VL - 19

SP - 1

EP - 17

JO - Bernoulli

JF - Bernoulli

IS - 1

ER -