fda.smoothdata: Functional Actigraphy Data Smoothing
In Actigraphy: Actigraphy Data Analysis

Description Usage Arguments Details Value Author(s) Examples

This function produces functional actigraphy data from matrix actigraphy data.

1	fda.smoothdata(data, basistype="fourier", nbasis=9, norder=4)

`data`	A list consisting of the following two components: `data$mat` A matrix where rows represent the time, columns are the samples, and the column names are the subjects. `data$cov` A two column matrix that contains the actigraphy data and clinical covariate.
`basistype`	A string specifying either `"Fourier"` and `"bspline"`.
`nbasis`	The number of basis functions to be used for functional data. Default value is 9.
`norder`	The order of the bspline basis functions. Default value is 4.

Note: The output of function fda.matchid can be directly used as the input for this argument.
If the data is a categorical covariate

A list consisting of two components as follows:

`fd`	A `fdSmooth` data object containing the functional data (see function `smooth.basis` in the package `fda` for details).
`cov`	An object that is the same as the argument `data$cov`.

William D. Shannon, Tao Li, Hong Xian, Jia Wang, Elena Deych, Carlos Gonzalez

	data(act_29pt)
	data(clinic_29pt_ahi)
	
	data <- act_29pt
	ahi <- clinic_29pt_ahi
	
	matchid  <- fda.matchid(data, ahi, "contin")
	FDcont <- fda.smoothdata(matchid)
	
	### Smooth the Results
	ts.plot(predict(FDcont$fd$fd, 1:1440), main="Smoothed Activity Data")