dclone-package: Data Cloning
Description
Low level functions for implementing
maximum likelihood estimating procedures for
complex models using data cloning (Lele et al. 2007) and Bayesian
Markov chain Monte Carlo methods with support
for JAGS, WinBUGS and OpenBUGS.
Parallel computing with JAGS is supported.
Main functions include:
dclone, dcdim: cloning R objects in various ways.
jags.fit, bugs.fit: conveniently fit BUGS models.
(jags.parfit fits chains on parallel workers for JAGS.)
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:
convenient functions for mcmc.list objects.
write.jags.model, clean.jags.model,
custommodel:
convenient functions for handling BUGS models.References
Solymos, P., 2010. dclone: Data Cloning in R.
The R Journal 2(2), 29--37.
URL: http://journal.r-project.org/
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
xx, in press.