Help for package rrandvec (original) (raw)
| 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. |
| Version: | 1.0.0 |
| Depends: | R (≥ 3.1.0) |
| Imports: | Rcpp, checkmate |
| Suggests: | covr, testthat, scatterplot3d |
| License: | BSD_2_clause + file LICENSE |
| URL: | https://jakobbossek.github.io/rrandvec/,https://github.com/jakobbossek/rrandvec |
| BugReports: | https://github.com/jakobbossek/rrandvec/issues |
| Encoding: | UTF-8 |
| ByteCompile: | true |
| RoxygenNote: | 7.2.3 |
| LinkingTo: | Rcpp |
| NeedsCompilation: | yes |
| Packaged: | 2023-03-29 15:42:20 UTC; bossek |
| Author: | Jakob Bossek  [aut, cre, cph] |
| Maintainer: | Jakob Bossek j.bossek@gmail.com |
| Repository: | CRAN |
| Date/Publication: | 2023-03-30 07:10:02 UTC |
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)
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")
}