PEER.Sim: Simulated longitudinal data with functional predictor and...
In refund: Regression with Functional Data
PEER.Sim R Documentation
Simulated longitudinal data with functional predictor and scalar response,
and structural information associated with predictor function
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)
refund documentation built on Sept. 21, 2024, 1:07 a.m.
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| PEER.Sim | R Documentation |
Simulated longitudinal data with functional predictor and scalar response, and structural information associated with predictor function
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)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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