fitted.FPCAder: Fitted functional data for derivatives from the FPCAder...

In fdapace: Functional Data Analysis and Empirical Dynamics

Fitted functional data for derivatives from the FPCAder object

Description

Combines the zero-meaned fitted values and the mean derivative to get the fitted values for the derivative trajectories. Estimates are given on the work-grid, not on the observation grid. Use ConvertSupport to map the estimates to your desired domain.

Usage

## S3 method for class 'FPCAder'
fitted(object, K = NULL, ...)

Arguments

object	A object of class FPCA returned by the function FPCA().
K	The integer number of the first K components used for the representation. (default: length(derObj$lambda ))
...	Additional arguments

Value

An n by length(workGrid) matrix, each row of which contains a sample.

References

Liu, Bitao, and Hans-Georg Müller. "Estimating derivatives for samples of sparsely observed functions, with application to online auction dynamics." Journal of the American Statistical Association 104, no. 486 (2009): 704-717. (Sparse data FPCA)

Examples

set.seed(1)
n <- 20
pts <- seq(0, 1, by=0.05)
sampWiener <- Wiener(n, pts)
sampWiener <- Sparsify(sampWiener, pts, 10)

fdapace documentation built on July 3, 2024, 5:08 p.m.