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Updates for JAGS 5.0.0 #174

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Updates for JAGS 5.0.0 #174

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22f37ec
Updates for ggplot2
martynplummer Feb 7, 2026
bf261fb
Updates for JAGS 5.0.0
martynplummer Feb 7, 2026
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2 changes: 1 addition & 1 deletion R/get_formula.R
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Original file line number Diff line number Diff line change
Expand Up @@ -152,7 +152,7 @@ get_formula_str = function(ST, par_x, ytype = "ct", init = FALSE) {
if (ytype == "ct") {
formula_str = paste0(formula_str, "\n\n# Fitted value\ny_[i_] = \n")
} else if (ytype == "sigma") {
formula_str = paste0(formula_str, "# Fitted standard deviation\nsigma_[i_] = max(0, \n") # Add max(0, [formula]) to prevent modeling negative sigmas. JAGS uses precision = 1 / sigma^2 which yields positive precisions for negative sigmas.
formula_str = paste0(formula_str, "# Fitted standard deviation\nsigma_[i_] = max(0.001, \n") # Add max(0, [formula]) to prevent modeling negative sigmas. JAGS uses precision = 1 / sigma^2 which yields positive precisions for negative sigmas.
} else if (stringr::str_detect(ytype, "ar[0-9]+")) {
formula_str = paste0(formula_str, "# Autoregressive coefficient for all AR(", ar_order,")\n", ytype, "_[i_] = \n")
} else if (stringr::str_detect(ytype, "ma[0-9]+")) {
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4 changes: 3 additions & 1 deletion R/get_jagscode.R
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Expand Up @@ -145,7 +145,9 @@ get_jagscode = function(prior, ST, formula_str, arma_order, family, sample) {
# Compute residuals for AR
if (has_ar) {
if (family$family == "binomial") {
mm = paste0(mm, "\n resid_abs_[i_] = ", family$linkfun_str, "(", ST$y[1], "[i_] / ", ST$trials[1], "[i_]) - y_[i_] # Residuals represented by sigma_ after ARMA")
mm = paste0(mm, "\n resid_abs_[i_] = ", family$linkfun_str, "(0.01 + 0.98 * ", ST$y[1], "[i_] / ", ST$trials[1], "[i_]) - y_[i_] # Residuals represented by sigma_ after ARMA")
} else if (family$family == "poisson") {
mm = paste0(mm, "\n resid_abs_[i_] = ", family$linkfun_str, "(0.01 + ", ST$y[1], "[i_]) - y_[i_] # Residuals represented by sigma_ after ARMA")
} else {
mm = paste0(mm, "\n resid_abs_[i_] = ", family$linkfun_str, "(", ST$y[1], "[i_]) - y_[i_] # Residuals represented by sigma_ after ARMA")
}
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8 changes: 4 additions & 4 deletions tests/testthat/helper-runs.R
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Expand Up @@ -162,14 +162,14 @@ test_plot = function(fit, varying_cols) {
is_expected = any(stringr::str_detect(error_message, expected_error))
expect_true(is_expected)
} else {
testthat::expect_true(ggplot2::is.ggplot(gg))
testthat::expect_true(ggplot2::is_ggplot(gg))
}
}

# Test plot() calls to bayesplot
test_plot_pars = function(fit) {
gg = plot_pars(fit, type = "dens_overlay")
testthat::expect_true(ggplot2::is.ggplot(gg))
testthat::expect_true(ggplot2::is_ggplot(gg))
}


Expand All @@ -194,7 +194,7 @@ test_hypothesis = function(fit) {

# Varying
if (!is.null(fit$pars$varying)) {
mcmc_vars = colnames(mcmclist_samples(fit)[[1]])
mcmc_vars = colnames(mcp:::mcmclist_samples(fit)[[1]])
varying_starts = paste0("^", fit$pars$varying[1])
varying_col_ids = stringr::str_detect(mcmc_vars, varying_starts)
varying_cols = paste0("`", mcmc_vars[varying_col_ids], "`") # Add these for varying
Expand Down Expand Up @@ -298,7 +298,7 @@ test_pp_eval = function(fit) {
testthat::expect_true(error_message)
}
} else {
testthat::expect_true(ggplot2::is.ggplot(pp_default))
testthat::expect_true(ggplot2::is_ggplot(pp_default))
}
}

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