fdapace (version 0.6.0)

CreatePathPlot: Create the fitted sample path plot based on the results from FPCA().

Description

Create the fitted sample path plot based on the results from FPCA().

Usage

CreatePathPlot(
  fpcaObj,
  subset,
  K = NULL,
  inputData = fpcaObj[["inputData"]],
  showObs = !is.null(inputData),
  obsOnly = FALSE,
  showMean = FALSE,
  derOptns = list(p = 0),
  ...
)

Arguments

fpcaObj

Returned object from FPCA().

subset

A vector of indices or a logical vector for subsetting the observations.

K

The number of components to reconstruct the fitted sample paths.

inputData

A list of length 2 containing the sparse/dense (unsupported yet) observations. inputData needs to contain two fields: Lt for a list of time points and Ly for a list of observations. Default to the `inputData` field within `fpcaObj`.

showObs

Whether to plot the original observations for each subject.

obsOnly

Whether to show only the original curves.

showMean

Whether to plot the mean function as a bold solid curve.

derOptns

A list of options to control derivation parameters; see `fitted.FPCA'. (default = NULL)

...

other arguments passed into matplot for plotting options

Examples

set.seed(1)
n <- 20
pts <- seq(0, 1, by=0.05)
sampWiener <- Wiener(n, pts)
sampWiener <- Sparsify(sampWiener, pts, 10)
res <- FPCA(sampWiener$Ly, sampWiener$Lt, 
            list(dataType='Sparse', error=FALSE, kernel='epan',
            verbose=TRUE))
CreatePathPlot(res, subset=1:5)

# CreatePathPlot has a lot of usages:
# \donttest{
CreatePathPlot(res)
CreatePathPlot(res, 1:20)
CreatePathPlot(res, 1:20, showObs=FALSE)
CreatePathPlot(res, 1:20, showMean=TRUE, showObs=FALSE)
CreatePathPlot(res, 1:20, obsOnly=TRUE)
CreatePathPlot(res, 1:20, obsOnly=TRUE, showObs=FALSE)
CreatePathPlot(inputData=sampWiener, subset=1:20, obsOnly=TRUE)# }