corvectors | R Documentation |

`corvectors()`

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

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

`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 |

`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 |

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.

`corvectors()`

returns a matrix given the specified multivariate relation.

Pascal van Kooten and Gerko Vink

## 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)

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.