samplr: Compare Human Performance to Sampling Algorithms

Understand human performance from the perspective of sampling, both looking at how people generate samples and how people use the samples they have generated. A longer overview and other resources can be found at <https://sampling.warwick.ac.uk>.

Version: 1.0.1
Depends: R (≥ 2.10)
Imports: Rcpp (≥ 1.0.6), ggplot2, latex2exp, pracma, stats, lme4, Rdpack, R6, graphics
LinkingTo: Rcpp, RcppArmadillo, RcppDist, testthat
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0), vdiffr, bench, dplyr, tidyr, magrittr, mvtnorm, xml2, samplrData
Published: 2024-08-19
DOI: 10.32614/CRAN.package.samplr
Author: Lucas Castillo ORCID iD [aut, cre, cph], Yun-Xiao Li ORCID iD [aut, cph], Adam N Sanborn ORCID iD [aut, cph], European Research Council (ERC) [fnd]
Maintainer: Lucas Castillo <lucas.castillo-marti at warwick.ac.uk>
BugReports: https://github.com/lucas-castillo/samplr/issues
License: CC BY 4.0
URL: https://github.com/lucas-castillo/samplr
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: samplr results

Documentation:

Reference manual: samplr.pdf
Vignettes: Simulations-of-the-Autocorrelated-Bayesian-Sampler (source, R code)
custom-density-functions (source, R code)
how-to-sample (source, R code)
multivariate-mixtures (source, R code)
samplr-package (source, R code)
supported-distributions (source, R code)
time-comparisons (source, R code)

Downloads:

Package source: samplr_1.0.1.tar.gz
Windows binaries: r-devel: samplr_1.0.1.zip, r-release: samplr_1.0.1.zip, r-oldrel: samplr_1.0.1.zip
macOS binaries: r-release (arm64): samplr_1.0.1.tgz, r-oldrel (arm64): samplr_1.0.1.tgz, r-release (x86_64): samplr_1.0.1.tgz, r-oldrel (x86_64): samplr_1.0.1.tgz
Old sources: samplr archive

Linking:

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