# mlappx: Multilinear interpolation on a grid In chebpol: Multivariate Interpolation

## Description

Multilinear interpolation on an arbitrary Cartesian product.

## Usage

 1 mlappx(...)

## Arguments

 ... Further arguments to the function, if is.function(val). val Array or function. Function values on a grid, or the function itself. If it is the values, the dim-attribute must be appropriately set. grid A list. Each element is a vector of ordered grid-points for a dimension. These need not be Chebyshev-knots, nor evenly spaced.

## Details

A call fun <- mlappx(val,grid) creates a multilinear interpolant on the grid. The value on the grid points will be exact, the value between the grid points is a convex combination of the values in the corners of the hypercube surrounding it.

If val is a function it will be evaluated on the grid.

## Value

A function(x) defined on the hypercube, approximating the given function. The function yields values for arguments outside the hypercube as well, as a linear extension.

## Examples

 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 ## Not run: ## evenly spaced grid-points su <- seq(0,1,length.out=10) ## irregularly spaced grid-points s <- su^3 ## create approximation on the irregularly spaced grid ml1 <- Vectorize(mlappx(exp,list(s))) ## test it, since exp is convex, the linear approximation lies above ## the exp between the grid points ml1(su) - exp(su) ## multi linear approx f <- function(x) exp(sum(x^2)) grid <- list(s,su) ml2 <- mlappx(evalongrid(f,grid=grid),grid) # an equivalent would be ml2 <- mlappx(f,grid) a <- runif(2); ml2(a); f(a) # we also get an approximation outside of the domain, of disputable quality ml2(c(1,2)); f(c(1,2)) ## End(Not run)

### Example output

[1] 0.0000000000 0.0007963441 0.0023666771 0.0036681447 0.0028930495
[6] 0.0111173403 0.0064666457 0.0191999204 0.0246303860 0.0000000000
[1] 3.563118
[1] 3.36368
[1] 19.97883
[1] 148.4132

chebpol documentation built on Dec. 9, 2019, 5:08 p.m.