Package 'rrandvec' reference manual

Title:	Generate Random Vectors Whose Components Sum Up to One
Description:	A single method implementing multiple approaches to generate pseudo-random vectors whose components sum up to one (see, e.g., Maziero (2015) <doi:10.1007/s13538-015-0337-8>). The components of such vectors can for example be used for weighting objectives when reducing multi-objective optimisation problems to a single-objective problem in the socalled weighted sum scalarisation approach.
Authors:	Jakob Bossek [aut, cre, cph]
Maintainer:	Jakob Bossek <[email protected]>
License:	BSD_2_clause + file LICENSE
Version:	1.0.0
Built:	2024-11-07 02:40:27 UTC
Source:	https://github.com/jakobbossek/rrandvec

Generate random vectors that sum up to one.

Description

Generate an $n \times d$ matrix. Each row vector is a probability vector $(p_1, \ldots, p_d)$ with $\sum_{i=1}^{d} p_i = 1$ . The function offers several methods to generate the rows in a way that the components are unbiased which means that they are required to have similar / the same probability distributions.

[1] Maziero, J. Generating Pseudo-Random Discrete Probability Distributions. Brazilian Journal of Physics 45, 377–382 (2015). https://doi.org/10.1007/s13538-015-0337-8

[2] Grimme, C. Picking a Uniformly Random Point from an Arbitrary Simplex. Technical Report. https://doi.org/10.13140/RG.2.1.3807.6968

Usage

rrandvec(n, d, method = "normalization", shuffle = FALSE, as.df = FALSE)
rrandvec(n, d, method = "normalization", shuffle = FALSE, as.df = FALSE)

Arguments

`n`	[`integer(1)`] Number of vectors to generate.
`d`	[`integer(1)`] Number of components of each vector (at least 2).
`method`	[`character(1)`] One of “norm” (normalization method), “trigonometric”, “simplex” (sample from a unit simplex), “exponential” or “iterative”. Default is `simplex`.
`shuffle`	[`logical(1)`] Should the values of each vector be permutatet randomly? Background: methods “iterative” and “trigonometric” introduce unwanted bias (see desciption). This issue can be alliviated by random shuffling. Default is `FALSE`.
`as.df`	[`logical(1)`] Should the return value be a data frame with column names X1 to Xd? Default is `FALSE`.

Value

[matrix(n, d)] $(n \times d)$ matrix even if $n=1$ .

Examples

R = rrandvec(1000, 2)
R = rrandvec(1000, 5, method ="iterative")
R = rrandvec(1000, 3, method = "trigonometric", shuffle = TRUE, as.df = TRUE)

if (require("scatterplot3d")) {
  scatterplot3d::scatterplot3d(R, angle = 120, cex.symbols = 0.5, pch = 3, color = "blue")
}
R = rrandvec(1000, 2)
R = rrandvec(1000, 5, method ="iterative")
R = rrandvec(1000, 3, method = "trigonometric", shuffle = TRUE, as.df = TRUE)

if (require("scatterplot3d")) {
  scatterplot3d::scatterplot3d(R, angle = 120, cex.symbols = 0.5, pch = 3, color = "blue")
}