exportPattern("^[[:alpha:]]+")
#export(gesm, mcmc.gesm, summary.gesm, fmem, mcmc.fmem, summary.fmem, bsp, bsp.graph)
import(splines, truncdist, GIGrvg, normalp, Formula)

#export(gesm, mcmc.gesm, summary.gesm, fmem, mcmc.fmem, summary.fmem, bsp, bsp.graph, bsp.graph.fmem)

#export(gesm, mcmc.gesm, summary.gesm, fmem, mcmc.fmem, summary.fmem, bsp, bsp.graph.gesm, bsp.graph.fmem)

importFrom("stats", "dbeta", "optim", "pbeta", "qbeta", "rbeta",

"rbinom", "runif", "sd", "var","dgamma", "dnorm",
"pgamma", "pnorm", "qgamma", "qnorm", "rgamma", "rnorm", "rpois")

exportPattern("Alzheimer", "as.mcmc.blca.gibbs", "blca", "blca.boot", "blca.em", "blca.em.se", "blca.gibbs", "blca.vb", "data.blca", "MAP", "rlca", "unMAP", "Zscore")

exportPattern("Alzheimer", "as.mcmc.blca.gibbs", "blca", "blca.boot", "blca.em", "blca.em.sd", "blca.gibbs", "blca.vb", "data.blca", "MAP", "rlca", "unMAP", "Zscore")

exportPattern("Alzheimer", "blca", "blca.boot", "blca.em", "blca.em.sd", "blca.gibbs", "blca.vb", "data.blca", "MAP", "rlca", "unMAP", "Zscore")

importFrom("graphics", "abline", "axis", "lines", "matplot", "mosaicplot", "mtext", "plot")
importFrom("stats", "dbeta", "dbinom", "density", "rbeta", "rmultinom", "runif", "sd", "var", "weighted.mean")

# Tell R to load the shared object <BayesLogit.so>.
useDynLib("BayesLogit")
# Define which functions people can see.
export(logit, logit.EM, mlogit, rpg.gamma,  rpg.devroye, rks);
# For testing purposes.
# logit.R, logit.EM.R, mlogit.R, rpg.gamma.R, rpg.devroye.R

export(logit, logit.EM, mlogit, rpg.gamma, rpg.devroye, rks,
#export(logit, logit.EM, mlogit, rpg.gamma, rpg.devroye, rks,
#       FFBS.R, FFBS.C, CUBS.R, CUBS.C, ar1.llh.C,

logit.combine, mlogit.combine, rpg.alt, rpg.sp, rpg,
importFrom("stats", "pgamma", "pnorm", "rexp", "rgamma", "rnorm",

# export(logit.R, logit.EM.R, rpg.gamma, rpg.devroye, rpg.alt, rpg.sp, rpg)

importFrom(stats, qbeta, qnorm, qt, uniroot)

export(bayesmixsurv, bayesmixsurv.crossval, bayesmixsurv.crossval.wrapper, bayesmixsurv.generate.folds, bayesmixsurv.generate.folds.eventbalanced, bayesmixsurv.control)
importFrom("stats", ".getXlevels", "acf", "delete.response", "dgamma",
"quantile", "rexp", "rgamma", "runif", "sd")