roll_apply_par: Rolling apply a function on a data frame or matrix.

In fountainer/fountainr: Functions used for myself

Description

Rolling apply a function on a data frame or matrix.

Usage

roll_apply_par(data, width, FUN, ..., parallel = FALSE, .export = NULL,
  .packages = NULL, progress = FALSE)

Arguments

data	A data frame or a matrix.
width	The rolling windown size.
FUN	function whose first parameter is the data.
...	Additional parameter passed to FUN
parallel	parallel computing. Default is FALSE. If parallel is positive, parallel is the number of cores. If parallel is negative, the number of cores is detectCores() + parallel
.export	character vector of variables to export. Default is NULL.
.packages	character vector of packages that tasks depends on.
progress	Create a progress bar. Default FALSE.

Value

A list of result.

Examples

res <- roll_apply_par(matrix(seq(10^4 * 3), ncol = 3), 100, function(m) eigen(cov(m))$values, parallel = TRUE, progress = TRUE)

fountainer/fountainr documentation built on May 16, 2019, 1:51 p.m.