Package: dclone 2.3-3

dclone: Data Cloning and MCMC Tools for Maximum Likelihood Methods

Low level functions for implementing maximum likelihood estimating procedures for complex models using data cloning and Bayesian Markov chain Monte Carlo methods as described in Solymos 2010 <doi:10.32614/RJ-2010-011>. Sequential and parallel MCMC support for 'JAGS', 'WinBUGS', 'OpenBUGS', and 'Stan'.

Authors:Peter Solymos [aut, cre]

dclone_2.3-3.tar.gz
dclone_2.3-3.zip(r-4.5)dclone_2.3-3.zip(r-4.4)dclone_2.3-3.zip(r-4.3)
dclone_2.3-3.tgz(r-4.4-any)dclone_2.3-3.tgz(r-4.3-any)
dclone_2.3-3.tar.gz(r-4.5-noble)dclone_2.3-3.tar.gz(r-4.4-noble)
dclone_2.3-3.tgz(r-4.4-emscripten)dclone_2.3-3.tgz(r-4.3-emscripten)
dclone.pdf |dclone.html✨
dclone/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/datacloning/dclone/issues

Uses libs:
  • jags– Just Another Gibbs Sampler for Bayesian MCMC
  • c++– GNU Standard C++ Library v3
Datasets:
  • ovenbird - Abundances of ovenbird in Alberta
  • regmod - Exemplary MCMC list object

On CRAN:

6.91 score 7 stars 4 packages 217 scripts 572 downloads 9 mentions 81 exports 56 dependencies

Last updated 2 months agofrom:9512985f64. Checks:OK: 3 NOTE: 4. Indexed: no.

TargetResultDate
Doc / VignettesOKOct 24 2024
R-4.5-winOKOct 24 2024
R-4.5-linuxOKOct 24 2024
R-4.4-winNOTEOct 24 2024
R-4.4-macNOTEOct 24 2024
R-4.3-winNOTEOct 24 2024
R-4.3-macNOTEOct 24 2024

Exports:.dcFitas.mcmc.list.bugsbugs.fitbugs.parfitchisq.diagchisq.diag.mcmc.listclean.jags.modelclearDcloneEnvclusterSizeclusterSplitSBcodaSamplescoef.mcmc.listconfint.mcmc.list.dccustommodeldc.fitdc.parfitdcdiagdcdiag.defaultdcdimdciiddclonedclone.dcdimdclone.dciiddclone.dctrdclone.defaultdclone.environmentdclone.listdcoptionsdcsddcsd.mcmc.listdctabledctable.defaultdctrerrlineserrlines.defaultevalParallelArgumentexistsDcloneEnvextractdcdiagextractdcdiag.defaultextractdctableextractdctable.defaultjags.fitjags.parfitjagsModellambdamax.diaglambdamax.diag.mcmc.listlistDcloneEnvmake.symmetricmclapplySBmcmcapplynclonesnclones.defaultnclones.listpairs.mcmc.listparallel.initsparCodaSamplesparDosaparJagsModelparLapplySBparLapplySLBparListFactoriesparListModulesparLoadModuleparSetFactoryparUnloadModuleparUpdateplot.dcdiagplot.dctableplotClusterSizepullDcloneEnvpushDcloneEnvquantile.mcmc.liststack.mcmc.liststan.fitstan.modelstan.parfitupdate.mcmc.listupdated.modelvcov.mcmc.listvcov.mcmc.list.dcwrite.jags.model

Dependencies:abindbackportsBHbootcallrcheckmateclicodacolorspacedescdistributionalfansifarvergenericsggplot2gluegridExtragtableinlineisobandlabelinglatticelifecycleloomagrittrMASSMatrixmatrixStatsmgcvmunsellnlmenumDerivpillarpkgbuildpkgconfigposteriorprocessxpsQuickJSRR2OpenBUGSR6RColorBrewerRcppRcppEigenRcppParallelrjagsrlangrstanscalesStanHeaderstensorAtibbleutf8vctrsviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
Data Cloningdclone-package
Internal function for iterative model fitting with data cloning.dcFit
Fit BUGS models with cloned dataas.mcmc.list.bugs bugs.fit
Parallel computing with WinBUGS/OpenBUGSbugs.parfit
Optimizing the number of workersclusterSize plotClusterSize
Size balancingclusterSplitSB parLapplySB parLapplySLB
Generate posterior samples in mcmc.list formatcodaSamples
Iterative model fitting with data cloningdc.fit
Parallel model fitting with data cloningdc.parfit
Cloning R objectsdcdim dciid dclone dclone.dcdim dclone.dciid dclone.dctr dclone.default dclone.environment dclone.list dctr
Manipulating dclone environments.DcloneEnvModel .DcloneEnvResults clearDcloneEnv DcloneEnv existsDcloneEnv listDcloneEnv pullDcloneEnv pushDcloneEnv
Setting Optionsdcoptions
Retrieve descriptive statistics from fitted objects to evaluate convergencedcdiag dcdiag.default dctable dctable.default extractdcdiag extractdcdiag.default extractdctable extractdctable.default plot.dcdiag plot.dctable
Plot error barserrlines errlines.default
Evaluates parallel argumentevalParallelArgument
Fit JAGS models with cloned datajags.fit
Parallel computing with JAGSjags.parfit
Create a JAGS model objectjagsModel
Data Cloning Diagnosticschisq.diag chisq.diag.mcmc.list lambdamax.diag lambdamax.diag.mcmc.list
Make a square matrix symmetric by averaging.make.symmetric
Size balancing version of mclapplymclapplySB
Methods for the 'mcmc.list' classcoef.mcmc.list confint.mcmc.list.dc dcsd dcsd.mcmc.list quantile.mcmc.list vcov.mcmc.list vcov.mcmc.list.dc
Calculations on 'mcmc.list' objectsmcmcapply stack.mcmc.list
Number of Clonesnclones nclones.default nclones.list
Abundances of ovenbird in Albertaovenbird
Scatterplot Matrices for 'mcmc.list' Objectspairs.mcmc.list
Parallel RNGs for initial valuesparallel.inits
Generate posterior samples in 'mcmc.list' format on parallel workersparCodaSamples
Parallel wrapper function to call from within a functionparDosa
Create a JAGS model object on parallel workersparJagsModel
Dynamically load JAGS modules on parallel workersparListModules parLoadModule parUnloadModule
Advanced control over JAGS on parallel workersparListFactories parSetFactory
Update jags models on parallel workersparUpdate
Exemplary MCMC list objectregmod
Fit Stan models with cloned datastan.fit stan.model stan.parfit
Automatic updating of an MCMC object from JAGSupdate.mcmc.list updated.model
Write and remove model fileclean.jags.model custommodel write.jags.model