Description

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.

Format

The data frame PEER.Sim is made up of subject ID number(id), subject-specific time of measurement (t), functional predictor profile (W.1-W.100) and scalar response (Y)

Details

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).

References

Kundu, M. G., Harezlak, J., and Randolph, T. W. (2012). Longitudinal functional models with structured penalties. (please contact J. Harezlak at harezlak@iupui.edu)