ftsa (version 3.2)

pcscorebootstrapdata: Bootstrap independent and identically distributed functional data or functional time series

Description

Computes bootstrap or smoothed bootstrap samples based on either independent and identically distributed functional data or functional time series.

Usage

pcscorebootstrapdata(dat, bootrep, statistic, bootmethod = c("st", "sm", "mvn", 
 "stiefel"), smo)

Value

bootdataBootstrap samples. If the original data matrix is $p$ by $n$, then the bootstrapped data are $p$ by $n$ by $bootrep$.meanfunctionBootstrap summary statistics. If the original data matrix is $p$ by $n$, then the bootstrapped summary statistics is $p$ by $bootrep$.

Details

We will presume that each curve is observed on a grid of $T$ points with $0\leq t_1

References

D. S. Poskitt and A. Sengarapillai (2012), "Description length and dimensionality reduction in functional data analysis", Computational Statistics and Data Analysis, in press.

See Also

fbootstrap

Examples

boot1 = pcscorebootstrapdata(ElNino$y, 500, "mean", bootmethod = "st")
boot2 = pcscorebootstrapdata(ElNino$y, 500, "mean", bootmethod = "sm", smo = 0.05)
boot3 = pcscorebootstrapdata(ElNino$y, 500, "mean", bootmethod = "mvn")
boot4 = pcscorebootstrapdata(ElNino$y, 500, "mean", bootmethod = "stiefel")