Package: nimbleNoBounds 1.0.3

nimbleNoBounds: Transformed Distributions for Improved MCMC Efficiency

A collection of common univariate bounded probability distributions transformed to the unbounded real line, for the purpose of increased MCMC efficiency.

Authors:David Pleydell [aut, cre, cph]

nimbleNoBounds_1.0.3.tar.gz
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nimbleNoBounds_1.0.3.tgz(r-4.4-any)nimbleNoBounds_1.0.3.tgz(r-4.3-any)
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nimbleNoBounds.pdf |nimbleNoBounds.html
nimbleNoBounds/json (API)

# Install 'nimbleNoBounds' in R:
install.packages('nimbleNoBounds', repos = c('https://drjp.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/drjp/nimblenobounds/issues

Datasets:

On CRAN:

18 exports 1 stars 0.98 score 16 dependencies 2 scripts 827 downloads

Last updated 3 months agofrom:e7e6a88db2. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 04 2024
R-4.5-winOKSep 04 2024
R-4.5-linuxOKSep 04 2024
R-4.4-winOKSep 04 2024
R-4.4-macOKSep 04 2024
R-4.3-winOKSep 04 2024
R-4.3-macOKSep 04 2024

Exports:dLogChisqdLogExpdLogGammadLogHalfflatdLogInvgammadLogitBetadLogitUnifdLogLnormdLogWeibrLogChisqrLogExprLogGammarLogHalfflatrLogInvgammarLogitBetarLogitUnifrLogLnormrLogWeib

Dependencies:clicodacpp11glueigraphlatticelifecyclemagrittrMatrixnimblenumDerivpkgconfigpracmaR6rlangvctrs

A quick guide to nimbleNoBounds

Rendered fromnimbleNoBounds.Rmdusingknitr::rmarkdownon Sep 04 2024.

Last update: 2023-11-29
Started: 2022-03-29