approximate: Approximate function with a spline
In richfitz/approximate: Approximate Functions With Interpolation

Description Usage Arguments Author(s)

View source: R/approximate.R

Approximate a function by a spline, refined to a given tolerance

approximate(target, a, b, ..., method = "fmm", n_base = 17L,
  max_depth = 16L, atol = tol, rtol = tol, verbose = FALSE,
  tol = sqrt(.Machine$double.eps), target_vectorised = TRUE,
  inverse = FALSE)

`target`	A function to approximate
`a`	The lower bound of the interpolation
`b`	The upper bound of the interpolation
`...`	Additional arguments passed through to `target`
`method`	The method of interpolation to used; passed through to `splinefun`
`n_base`	The number of equally spaced points to start with
`max_depth`	The number of times the base points will be subdivided, at most.
`atol`	The absolute tolerance; used to determine how the approximation is doing for values with small absolute value.
`rtol`	The relative tolerance' used to determine how the approximation is doing for values with large absolute value.
`verbose`	Be verbose when fitting the spline? This might be useful on expensive functions.
`tol`	The default value for `atol` and `rtol`; use this to set both at once.
`target_vectorised`	Flag indicating if `target` can accept a vector of `x` values; the default, `TRUE`, assumes that it can. If your function requires each `x` value separately set this to `FALSE`.
`inverse`	Indicates if the inverse approximate function is required. This is useful if you can use `target` to map x to y but you want the inverse mapping back. `a` and `b` will be the domain of `x` still (so the range of `y`, and the domain of the returned function).