Nothing
## -----------------------------------------------------------------------------
## Load package
library(dalmatian)
## -----------------------------------------------------------------------------
## Load gamma data
data(gamma_data_1)
## -----------------------------------------------------------------------------
## Define mean and variance objects
mymean <- list(fixed = list(name = "alpha",
formula = ~x1,
priors = list(c("dnorm",0,.001))),
random = list(name = "epsilon",
formula = ~ID - 1),
link = "log")
mydisp <- list(fixed = list(name = "psi",
formula = ~x2,
priors = list(c("dnorm",0,.001))),
random = list(name = "xi",
formula = ~ID - 1),
link = "log")
## ---- eval = FALSE------------------------------------------------------------
#
# ## Set working directory
# ## By default uses a system temp directory. You probably want to change this.
# workingDir <- tempdir()
#
# ## Define list of arguments for jags.model()
# jm.args <- list(file=file.path(workingDir,"gamma_test_1.R"),n.chains = 3, n.adapt = 1000)
#
# ## Define list of arguments for coda.samples()
# cs.args <- list(n.iter=5000,thin=20)
#
# ## Run the model using dalmatian
# gmcmc <- dalmatian(df=gamma_data_1,
# family = "gamma",
# mean.model=mymean,
# dispersion.model=mydisp,
# jags.model.args=jm.args,
# coda.samples.args=cs.args,
# response = "y",
# residuals = FALSE,
# run.model = TRUE,
# engine = "JAGS",
# n.cores = 3,
# overwrite = TRUE,
# saveJAGSinput = workingDir)
## ---- echo = FALSE------------------------------------------------------------
load(system.file("gresults.RData",package="dalmatian"))
## ---- eval = FALSE------------------------------------------------------------
# ## Compute convergence diagnostics
# gconvergence <- convergence(gmcmc)
#
## -----------------------------------------------------------------------------
## Gelman-Rubin diagnostics
gconvergence$gelman
## Raftery diagnostics
gconvergence$raftery
## Effective sample size
gconvergence$effectiveSize
## ---- eval = FALSE------------------------------------------------------------
# ## Generate traceplots
# ## gtraceplots <- traceplots(gmcmc,show=FALSE)
#
## ----fig.width=6,fig.align="center"-------------------------------------------
## Fixed effects for mean
gtraceplots$meanFixed
## Fixed effects for dispersion
gtraceplots$dispersionFixed
## ---- eval = FALSE------------------------------------------------------------
# ## Compute numerical summaries
# gsummary <- summary(gmcmc)
## -----------------------------------------------------------------------------
## Print numerical summaries
gsummary
## ---- eval = FALSE------------------------------------------------------------
# ## Generate caterpillar
# gcaterpillar <- caterpillar(gmcmc,show = FALSE)
#
## ----fig.width=6,fig.align="center"-------------------------------------------
## Fixed effects for mean
gcaterpillar$meanFixed
## Fixed effects for dispersion
gcaterpillar$dispersionFixed
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