Nothing
data("jags_logit")
test_that("Simple model runs with mcmcCoefPlot", {
expect_silent(mcmcCoefPlot(jags_logit))
})
test_that("mcmcCoefPlot works with jags_logit", {
## mcmc
expect_silent(mcmcCoefPlot(coda::as.mcmc(jags_logit)[[1]]))
})
if (require("MCMCpack", quietly = TRUE)) {
## fitting the model with MCMCpack
mcmcpack_linear <- MCMCpack::MCMCregress(Y ~ X, b0 = 0, B0 = 0.001,
sigma.mu = 5, sigma.var = 10,
data = list(X = rnorm(100),
Y = rnorm(100, 5, 5)),
seed = 1)
## testing
test_that("mcmcCoefPlot works with mcmcpack", {
expect_silent(mcmcCoefPlot(mcmcpack_linear))
})
}
test_that("Simple model runs with mcmcCoefPlot with arguments", {
## running some expect silent tests for jags_logit
expect_silent(mcmcCoefPlot(jags_logit))
expect_silent(mcmcCoefPlot(jags_logit, pars = 'b', regex = T))
expect_silent(mcmcCoefPlot(jags_logit, pars = 'b', ci = .9, hpdi = T, regex = T))
## test against a value
med_df <- mcmcCoefPlot(jags_logit, pars = 'b', pointest = 'median', plot = F, regex = T)
value <- med_df[2, 1]
check_against <- 0.5273031
expect_equal(value, check_against, tolerance = 1e-4)
## running one more for regex = FALSE
expect_silent(mcmcCoefPlot(jags_logit, pars = c('b[1]', 'b[2]'), regex = FALSE))
})
test_that("Simple model runs with mcmcCoefPlot with sorting", {
med_df <- mcmcCoefPlot(jags_logit, pars = 'b', sort = T, plot = F, regex = T)
value <- med_df[3, 1]
check_against <- 0.6335488
expect_equal(value, check_against, tolerance = 1e-4)
})
test_that("mcmcCoefPlot errors work", {
expect_error(mcmcCoefPlot(jags_logit, pointest = 'man'))
expect_error(mcmcCoefPlot(jags_logit, hpdi = 2))
})
# dontrun(
# if (require("runjags", quietly = TRUE)) {
# ## Generate an example runjags interactive fitted model
# ## formatting the data for jags
# datalist <- list(X = model.matrix(~ X1 * X2, sim_data_interactive),
# Y = sim_data_interactive[, 3],
# N = nrow(sim_data_interactive))
#
# ## creating jags model
# model <- "model {
# for(i in 1 : N){
# Y[i] ~ dnorm(beta %*% X[i, ], tau);
# }
# for(i in 1:4) {
# beta[i] ~ dnorm(0, 0.001)
# }
# tau ~ dexp(1)
# }"
#
# ## fitting the model with runjags
# runjags_interactive <- runjags::run.jags(model = model, monitor = c("beta", "tau"),
# data = datalist, n.chains = 2, method = "rjags")
#
# ## testing
# test_that("mcmcCoefPlot works with multiple object types", {
# ## runjags
# expect_silent(mcmcCoefPlot(runjags_interactive))
# })
#
# rm(datalist, model)
# }
# )
#
# dontrun(
# pkgs <- c("rjags", "R2WinBUGS"),
#
# if (!all(sapply(pkgs, require, quietly = TRUE, character.only = TRUE))) {
# ## Generate an example BUGS fitted model object
# data(LINE, package = "rjags")
# LINE$recompile()
#
# ## fitting the model with jags
# bugs_model <- rjags::coda.samples(LINE, c("alpha", "beta", "sigma"),
# n.iter = 1000)
# bugs_model <- R2WinBUGS::as.bugs.array(sims.array = as.array(bugs_model))
#
# test_that("mcmcCoefPlot works with bugs", {
# expect_silent(mcmcCoefPlot(bugs_model))
# })
# }
# )
# Maintainer note 11/2021 - I commented out that earlier code I believe because
# of cran issues with size - Need to go in and figure out if can delete completely
# or modify
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