KE_trajSCB {longke}

KE_trajSCB

Description

Function used to derive simultaneous confidence band (SCB) for the predicted response trajectory

Usage

KE_trajSCB(KE.fit.object,nboot=500,alpha=0.05)

Arguments

KE.fit.object

An object whose class is KE (you can get it by letting ke = KE.fit())

nboot

Number of bootstrap sample size to construct SCB

alpha

Confidence level for bootstrap SCB of predicted response trajectory

Value

A list containing num.test elements where the num.test represents the number of testing subjects. Within each element, there is a list containing 3 elements:

se

A vector containing standard errors at each discrete measurement time

traj.upper

A vector containing upper bound of the testing subject at each measurement time

traj.lower

A vector containing lower bound of the testing subject at each measurement time

References

Wang S, Kim S, Cho H, Chang W. Nonparametric predictive model for sparse and irregular longitudinal data. (2023+)

Kim, S., Ryan Cho, H., & Kim, M. O. (2021). Predictive generalized varying‐coefficient longitudinal model. Statistics in Medicine, 40(28), 6243-6259.

See Also

KE_fit

Examples

t_all = 1:50
T1=c(1,25);T2=c(26,50)
data = datagen(ntotal=350,ntest=50,t_all=t_all,t_split=25,seed=1)
train = data$train
test = data$test
ke.fit = KE_fit(train=train,test=test,T1=T1,T2=T2,bw_time=1,bw_subj = 0.2)
ketraj.toy = KE_trajSCB(KE.fit.object = ke.fit,
            nboot=10,alpha=0.05)