Package: bmhe 0.1.0

bmhe: This Package Creates a Set of Functions Useful for Bayesian modelling

A set of utility functions that can be used to post-process BUGS or JAGS objects as well as other to facilitate various Bayesian modelling activities (including in HTA).

Authors:Gianluca Baio

bmhe_0.1.0.tar.gz
bmhe_0.1.0.zip(r-4.5)bmhe_0.1.0.zip(r-4.4)bmhe_0.1.0.zip(r-4.3)
bmhe_0.1.0.tgz(r-4.4-any)bmhe_0.1.0.tgz(r-4.3-any)
bmhe_0.1.0.tar.gz(r-4.5-noble)bmhe_0.1.0.tar.gz(r-4.4-noble)
bmhe_0.1.0.tgz(r-4.4-emscripten)bmhe_0.1.0.tgz(r-4.3-emscripten)
bmhe.pdf |bmhe.html✨
bmhe/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/giabaio/bmhe_utils/issues

On CRAN:

bayesian-statisticsbugscost-effectiveness-analysisjagstidyverse

2.90 score 2 stars 8 scripts 17 exports 77 dependencies

Last updated 1 days agofrom:cf98bc33da. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 17 2024
R-4.5-winOKNov 17 2024
R-4.5-linuxOKNov 17 2024
R-4.4-winOKNov 17 2024
R-4.4-macOKNov 17 2024
R-4.3-winOKNov 17 2024
R-4.3-macOKNov 17 2024

Exports:acfplotbetaParbetaPar2betaplotcoefplotdiagplotgammaPargammaplotilogitlogitlogitParlognParodds2probsORposteriorplotstatstraceplot

Dependencies:abindbackportsBCEABHbriocallrcheckmateclicodacolorspacecrayondescdiffobjdigestdistributionaldplyrevaluatefansifarverfsgenericsggplot2gluegridExtragtableinlineisobandjsonlitelabelinglatticelifecycleloomagrittrMASSMatrixmatrixStatsMCMCvismgcvmunsellnlmenumDerivoverlappingpillarpkgbuildpkgconfigpkgloadplyrposteriorpraiseprocessxpspurrrQuickJSRR6rbibutilsRColorBrewerRcppRcppEigenRcppParallelRdpackreshape2rlangrprojrootrstanscalesStanHeadersstringistringrtensorAtestthattibbletidyselectutf8vctrsviridisLitewaldowithr

Readme and manuals

Help Manual

Help pageTopics
Autocorrelation plotacfplot
Computes the parameters of a Beta distribution so that the mean and standard dev are the input (m,s)betaPar
Compute the parameters of a Beta distribution, given a prior guess for key parameters. Based on "Bayesian ideas and data analysis", page 100. Optimisation method to identify the values of a,b that give required conditions on the Beta distributionbetaPar2
Trial-and-error Beta plotbetaplot
Coefplot for the parameters in the modelcoefplot
Specialised diagnostic plotsdiagplot
Computes the parameters of a Gamma distribution so that the mean and standard dev are the input (m,s)gammaPar
Trial-and-error Gamma plotgammaplot
Computes the inverse logit of a number between -infinity and +infinityilogit
Computes the logit of a numberlogit
Computes the parameters of a Normal distribution _on the logit scale_, so that, _on the natural scale_, the range where most of the mass is included is between the input 'low' and 'upp'logitPar
Computes mean and variance of a logNormal distribution so that the parameters on the natural scale are mu and sigmalognPar
Makes a traceplot (eg to visualise MCMC simulations from multiple chains)mytraceplot
Maps from odds to probabilitiesodds2probs
Computes the odds ratio between two probabilitiesOR
Produces a plot of the values of the Gelman Rubin stats to determine visually convergence (and see clearly which node has reached it)plotGR
Various plots for the posteriors in a 'bugs' or 'jags' objectposteriorplot
Printing a bugs objectprint.bugs
Computes and prints summary statistics for a vector or matrix of simulated valuesstats
Computes and prints summary statistics for a vector or matrix of simulated values - tidyverse stylestats2
Tidyverse based function to do traceplotstraceplot