dclone-package {dclone}

Data Cloning

Description

Low level functions for implementing maximum likelihood estimating procedures for complex models using data cloning and Bayesian Markov chain Monte Carlo methods. Sequential and parallel MCMC support for JAGS, WinBUGS, OpenBUGS, and Stan.

Main functions include:

• dclone, dcdim, dciid, dctr: cloning R objects in various ways.

• jags.fit, bugs.fit, stan.fit: conveniently fit JAGS/BUGS/Stan models. jags.parfit, bugs.parfit, stan.parfit fits chains on parallel workers.

• dc.fit: iterative model fitting by the data cloning algorithm. dc.parfit is the parallelized version.

• dctable, dcdiag: helps evaluating data cloning convergence by descriptive statistics and diagnostic tools. (These are based on e.g. chisq.diag and lambdamax.diag.)

• coef.mcmc.list, confint.mcmc.list.dc, dcsd.mcmc.list, quantile.mcmc.list, vcov.mcmc.list.dc, mcmcapply, stack.mcmc.list: methods for mcmc.list objects.

• write.jags.model, clean.jags.model, custommodel: convenient functions for handling JAGS/BUGS/Stan models.

• jagsModel, codaSamples: basic functions from rjags package rewrote to recognize data cloning attributes from data (parJagsModel, parUpdate, parCodaSamples are the parallel versions).

Author(s)

Author: Peter Solymos

Maintainer: Peter Solymos, [e-mail]

References

Forum: https://groups.google.com/forum/#!forum/dclone-users

Issues: https://github.com/datacloning/dcmle/issues

Data cloning website: https://datacloning.org

Solymos, P., 2010. dclone: Data Cloning in R. The R Journal 2(2), 29–37. URL: https://journal.r-project.org/archive/2010-2/RJournal_2010-2_Solymos.pdf

Lele, S.R., B. Dennis and F. Lutscher, 2007. Data cloning: easy maximum likelihood estimation for complex ecological models using Bayesian Markov chain Monte Carlo methods. Ecology Letters 10, 551–563.

Lele, S. R., K. Nadeem and B. Schmuland, 2010. Estimability and likelihood inference for generalized linear mixed models using data cloning. Journal of the American Statistical Association 105, 1617–1625.