prepare.list {hero}

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 class 'list'
prepare(data, x, splines, m = 2, sparse = TRUE, ...)

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.

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.

Value

A prepared_list object.

Author(s)

Joshua French.

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)