hero (version 0.6)

prepare.list: Prepare data array for sandwich smooth

Description

prepare.list prepares a list of data for the sandwich smooth. The class of each element of the list must be identical. The dimensionality of data[[i]] and the length of x must match. Specifically, length(dim(data[[i]])) must equal length(x). The dimensionality of data[[i]] and the length of splines must match. Specifically, length(dim(data[[i]])) must equal length(splines). Note: If the splines are preassembled, these can be passed using the argument assembled so that this computation is not reperformed.

Usage

# S3 method for list
prepare(data, x, splines, m = 2, sparse = TRUE, ...)

Value

A prepared_list object.

Arguments

data

A list of numeric, matrix, or array objects.

x

A list of values at which to evaluate the basis functions. See Examples and Details.

splines

A list of spline objects (hero_bspline and hero_radspline). See Examples and Details.

m

A positive integer indicating order of the difference penalty.

sparse

A logical value indicating if the result should be a sparse version of the Matrix-class.

...

Not currently implemented.

Author

Joshua French.

Details

This function applies the functions prepare.numeric, prepare.matrix, and prepare.array to each element of the list, so relevant restrictions in the arguments may be found there.

References

Xiao, L. , Li, Y. and Ruppert, D. (2013), Fast bivariate P-splines: the sandwich smoother. J. R. Stat. Soc. B, 75: 577-599. <doi:10.1111/rssb.12007>

See Also

prepare.numeric, prepare.matrix, prepare.array

Examples

# generate and prepare 3d data
set.seed(9)
dat = lapply(1:3, function (i) generate.data3d())
x = dat[[1]]$x
data = lapply(dat, getElement, name = "data3d")
obj = prepare(data, x = x)
h = hero(obj)