# splineFunction2D: Calculate linear combinations of spline basis functions on... In MFPCA: Multivariate Functional Principal Component Analysis for Data Observed on Different Dimensional Domains

## Description

Given scores (coefficients), these functions calculate a linear combination of spline tensor basis functions on two-dimensional domains based on the `gam`/`bam` functions in the mgcv package. See Details.

## Usage

 ```1 2 3``` ```splineFunction2D(scores, argvals, bs, m, k) splineFunction2Dpen(scores, argvals, bs, m, k) ```

## Arguments

 `scores` A matrix of dimension `N x K`, representing the `K` scores (coefficients) for each of the `N` observations. `argvals` A list containing a two numeric vectors, corresponding to the x- and y-values, on which the functions should be defined. `bs` A vector of character strings (or a single character), the type of basis functions to be used. Please refer to `te` for a list of possible basis functions. `m` A numeric vector (or a single number), the order of the spline basis. See `s` for details. `k` A numeric vector (or a single number), the number of basis functions used. See `s` for details.

## Details

If the scores have been calculated based on an unpenalized tensor spline basis, the linear combination is computed based on the `gam` functions ((`splineFunction2D`)). If the scores were obtained using penalization, the expansion is calculated via bam (`splineFunction2Dpen`).

## Value

An object of class `funData` with `N` observations on the two-dimensional domain specified by `argvals`, corresponding to the linear combination of spline basis functions.

## Warning

The function `splineFunction2Dpen`, which relies on bam has not been tested with ATLAS/MKL/OpenBLAS.

`univExpansion`, `gam`, `splineBasis2D`