PEER.Sim

<code>PEER.Sim</code> 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. 

<code>Q</code> represents the 7 x 100 matrix where each row provides structural information about the functional predictor profile for data <code>PEER.Sim</code>. For specific details about the simulation and Q matrix, please refer to Kundu et. al. (2012).

PEER.Sim, Q

Methods for regression for functional
    data, including function-on-scalar, scalar-on-function, and
    function-on-function regression. Some of the functions are applicable to
    image data.

Lei Huang

refund

Regression with Functional Data

PEER.Sim, Q function

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

PEER.Sim, Q: Simulated longitudinal data with functional predictor and scalar response, and structural information associated with predictor function

Description

Usage

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References