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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 [aut, cre, cph], Yun-Xiao Li [aut, cph], Adam N Sanborn [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 |
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) |
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 |
Please use the canonical form https://CRAN.R-project.org/package=samplr to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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