ipol: Create an interpolating function from given values. Several...

In latentcor: Fast Computation of Latent Correlations for Mixed Data

Create an interpolating function from given values. Several interpolation methods are supported.

Description

Create an interpolating function from given values. Several interpolation methods are supported.

Usage

ipol(val, grid = NULL, ...)

Arguments

val	array or function. Function values on a grid.
grid	list. Each element is a vector of ordered grid-points for a dimension.
...	Further arguments to the function, if is.function(val). And some extra arguments for interpolant creation described in section Details.

Value

A function(x, threads=getOption('chebpol.threads')) defined on a hypercube, an interpolant for the given function. The argument x can be a matrix of column vectors which are evaluated in parallel in a number of threads. The function yields values for arguments outside the hypercube as well, though it will typically be a poor approximation. threads is an integer specifying the number of parallel threads which should be used when evaluating a matrix of column vectors.

Author(s)

Simen Gaure

Examples

## 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 <- ipol(exp(s), grid=list(s))
## test it, since exp is convex, the linear approximation lies above
## the exp between the grid points
ml1(su) - exp(su)

## multi dimensional approximation
f <- function(x) 10/(1+25*mean(x^2))
# a 3-dimensional 10x10x10 grid, first and third coordinate are non-uniform
grid <- list(s, su, sort(1-s))

# make multilinear spline.
ml2 <- ipol(array(apply(expand.grid(grid), 1, f), c(10, 10, 10)), grid=grid)
# make 7 points in R3 to test them on
m <- matrix(runif(3*7),3)
rbind(true=apply(m,2,f), ml=ml2(m))

latentcor documentation built on Sept. 6, 2022, 1:06 a.m.