Description Author(s) References
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 and OpenBUGS.
Main functions include:
dclone
, dcdim
, dciid
,
dctr
:
cloning R objects in various ways.
jags.fit
, bugs.fit
:
conveniently fit BUGS models.
jags.parfit
and bugs.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 BUGS
models.
jagsModel
, codaSamples
: basic functions
from rjags package rewrote to recognize data cloning
attributes from data (parJagsModel
,
parUpdate
, parCodaSamples
are the parallel versions).
Author: Peter Solymos
Maintainer: Peter Solymos, solymos@ualberta.ca
Solymos, P., 2010. dclone: Data Cloning in R. The R Journal 2(2), 29–37. URL: http://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.
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