KE_bwselection

Function used to perform leave-one-subject-out cross validation to select
 optimal time bandwidth (b_s) and trajectory bandwidth (b_w)

The proposed method aims at predicting the longitudinal mean response trajectory by a
kernel-based estimator. The kernel estimator is constructed by imposing weights based on
subject-wise similarity on L2 metric space between predictor trajectories as well as time proximity.
Users could also perform variable selections to derive functional predictors with predictive significance
by the proposed multiplicative model with multivariate Gaussian kernels.

Shixuan Wang 

longke

Nonparametric Predictive Model for Sparse and Irregular
Longitudinal Data

Seonjin Kim 

Hyunkeun Cho 

Won Chang 

KE_bwselection function

<dl><dt>data</dt>
<dd>A long format data matrix containing columns ordered by
time, subject ID, response, predictor1, predictor2, ...
where the measurement time of the longitudinal data should be discretized</dd>
<dt>bw_time</dt>
<dd>A numeric vector that contains the candidate time bandwidths</dd>
<dt>bw_subj</dt>
<dd>A numeric vector that contains the candidate trajectory bandwidths</dd>
<dt>T1</dt>
<dd>A measurement time domain where the functional predictors are measured within</dd>
<dt>T2</dt>
<dd>A measurement time domain where the functional response is of interest to predict</dd></dl>

Arguments

KE_bwselection — KE_bwselection

<dl>

<dt>data</dt>
<dd>A long format data matrix containing columns ordered by
time, subject ID, response, predictor1, predictor2, ...
where the measurement time of the longitudinal data should be discretized</dd>


<dt>bw_time</dt>
<dd>A numeric vector that contains the candidate time bandwidths</dd>


<dt>bw_subj</dt>
<dd>A numeric vector that contains the candidate trajectory bandwidths</dd>


<dt>T1</dt>
<dd>A measurement time domain where the functional predictors are measured within</dd>


<dt>T2</dt>
<dd>A measurement time domain where the functional response is of interest to predict</dd>

</dl>

KE_bwselection: KE_bwselection

Description

Usage

Value

Arguments

References

Examples