PEER.Sim contains simulated observations from 100 subjects, each
observed at 4 distinct timepoints. At each timepoint bumpy predictor
profile is generated randomly and the scalar response variable is generated
considering a time-varying regression function and subject intercept.
Accompanying the functional predictor and scalar response are the subject
ID numbers and time of measurements.
The data frame
PEER.Sim is made up of subject ID
id), subject-specific time of measurement (
functional predictor profile (
W.1-W.100) and scalar response
Q represents the 7 x 100 matrix where each row provides structural
information about the functional predictor profile for data
PEER.Sim. For specific details about the simulation and Q matrix,
please refer to Kundu et. al. (2012).
Kundu, M. G., Harezlak, J., and Randolph, T. W. (2012). Longitudinal functional models with structured penalties. (please contact J. Harezlak at email@example.com)