corvectors: Create multivariate data by permutation

In stevemisc: Steve's Miscellaneous Functions

Create multivariate data by permutation

Description

corvectors() is a function to obtain a multivariate dataset by specifying the relation between those specified variables.

Usage

corvectors(
  data,
  corm,
  tol = 0.005,
  conv = 10000,
  cores = 2,
  splitsize = 1000,
  verbose = FALSE,
  seed
)

Arguments

data	a data matrix containing the data
corm	A value containing the desired correlation or a vector or data matrix containing the desired correlations
tol	A single value or a vector of tolerances with length ncol(data) - 1. The default is 0.005
conv	The maximum iterations allowed. Defaults to 1000.
cores	The number of cores to be used for parallel computing
splitsize	The size to use for splitting the data
verbose	Logical statement. Default is FALSE
seed	An optional seed to set

Details

This is liberally copy-pasted from van Kooten and Vink's wonderful-but-no-longer-supported correlate package. They call it correlate() in their package, but I opt for corvectors() here.

Value

corvectors() returns a matrix given the specified multivariate relation.

Author(s)

Pascal van Kooten and Gerko Vink

Examples

## Not run: 
set.seed(8675309)
library(tibble)
# bivariate example, start with zero correlation
as_tibble(data.frame(corvectors(replicate(2, rnorm(100)), .5)))

# multivariate example
as_tibble(data.frame(corvectors(replicate(4, rnorm(100)), c(.5, .6, .7))))


## End(Not run)

stevemisc documentation built on Sept. 11, 2024, 5:23 p.m.