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easystats · Apr 19, 2022 · beb6588 · beb6588
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,7 +1,7 @@
 Type: Package
 Package: bayestestR
 Title: Understand and Describe Bayesian Models and Posterior Distributions
-Version: 0.12.0.2
+Version: 0.12.0.3
 Authors@R:
     c(person(given = "Dominique",
              family = "Makowski",

diff --git a/NEWS.md b/NEWS.md
@@ -1,4 +1,4 @@
-# bayestestR 0.12.0
+# bayestestR 0.12.5
 
 ## Breaking
 
@@ -8,6 +8,8 @@
 
 * All `distribution_*(random = FALSE)` functions now rely on `ppoints()`, which will result in slightly different results, especially with small `n`s.
 
+* Uncertainty estimation now defaults to `"eti"` (formerly was `"hdi"`).
+
 ## Canges
 
 * *bayestestR* functions now support `draws` objects from package *posterior*.

diff --git a/R/ci.R b/R/ci.R
@@ -90,7 +90,7 @@ ci <- function(x, ...) {
   } else if (tolower(method) %in% c("si")) {
     return(si(x, BF = BF, effects = effects, component = component, parameters = parameters, verbose = verbose, ...))
   } else {
-    stop("`method` should be 'ETI' (for equal-tailed interval),'HDI' (for highest density interval), `BCI` (for bias corrected and accelerated bootstrap intervals) or 'SI' (for support interval).")
+    stop(insight::format_message("`method` should be 'ETI' (for equal-tailed interval),'HDI' (for highest density interval), 'BCI' (for bias corrected and accelerated bootstrap intervals), 'SPI' (for shortest probability interval) or 'SI' (for support interval)."), call. = FALSE)
   }
 }
 

diff --git a/R/describe_posterior.R b/R/describe_posterior.R
@@ -4,8 +4,8 @@
 #'
 #' @param posteriors A vector, data frame or model of posterior draws.
 #' @param ci_method The type of index used for Credible Interval. Can be
-#'   `"HDI"` (default, see [bayestestR::hdi()]), `"ETI"`
-#'   (see [bayestestR::eti()]), `"BCI"` (see
+#'   `"ETI"` (default, see [bayestestR::eti()]), `"HDI"`
+#'   (see [bayestestR::hdi()]), `"BCI"` (see
 #'   [bayestestR::bci()]), `"SPI"` (see [bayestestR::spi()]), or
 #'   `"SI"` (see [bayestestR::si()]).
 #' @param test The indices of effect existence to compute. Character (vector) or
@@ -96,7 +96,7 @@ describe_posterior <- function(posteriors,
                                centrality = "median",
                                dispersion = FALSE,
                                ci = 0.95,
-                               ci_method = "hdi",
+                               ci_method = "eti",
                                test = c("p_direction", "rope"),
                                rope_range = "default",
                                rope_ci = 0.95,
@@ -111,7 +111,7 @@ describe_posterior <- function(posteriors,
                                 centrality = "median",
                                 dispersion = FALSE,
                                 ci = 0.95,
-                                ci_method = "hdi",
+                                ci_method = "eti",
                                 test = c("p_direction", "rope"),
                                 rope_range = "default",
                                 rope_ci = 0.95,
@@ -146,7 +146,7 @@ describe_posterior <- function(posteriors,
   # Uncertainty
 
   if (!is.null(ci)) {
-    ci_method <- match.arg(tolower(ci_method), c("hdi", "quantile", "ci", "eti", "si", "bci", "bcai"))
+    ci_method <- match.arg(tolower(ci_method), c("hdi", "spi", "quantile", "ci", "eti", "si", "bci", "bcai"))
     if (ci_method == "si") {
       uncertainty <- ci(x, BF = BF, method = ci_method, prior = bf_prior, ...)
     } else {
@@ -433,7 +433,7 @@ describe_posterior.numeric <- function(posteriors,
                                        centrality = "median",
                                        dispersion = FALSE,
                                        ci = 0.95,
-                                       ci_method = "hdi",
+                                       ci_method = "eti",
                                        test = c("p_direction", "rope"),
                                        rope_range = "default",
                                        rope_ci = 0.95,
@@ -482,7 +482,7 @@ describe_posterior.bayesQR <- function(posteriors,
                                        centrality = "median",
                                        dispersion = FALSE,
                                        ci = 0.95,
-                                       ci_method = "hdi",
+                                       ci_method = "eti",
                                        test = c("p_direction", "rope"),
                                        rope_range = "default",
                                        rope_ci = 0.95,
@@ -532,7 +532,7 @@ describe_posterior.draws <- function(posteriors,
                                      centrality = "median",
                                      dispersion = FALSE,
                                      ci = 0.95,
-                                     ci_method = "hdi",
+                                     ci_method = "eti",
                                      test = c("p_direction", "rope"),
                                      rope_range = "default",
                                      rope_ci = 0.95,
@@ -570,7 +570,7 @@ describe_posterior.effectsize_std_params <- function(posteriors,
                                                      centrality = "median",
                                                      dispersion = FALSE,
                                                      ci = 0.95,
-                                                     ci_method = "hdi",
+                                                     ci_method = "eti",
                                                      test = c("p_direction", "rope"),
                                                      rope_range = "default",
                                                      rope_ci = 0.95,
@@ -634,7 +634,7 @@ describe_posterior.get_predicted <- function(posteriors,
                                              centrality = "median",
                                              dispersion = FALSE,
                                              ci = 0.95,
-                                             ci_method = "hdi",
+                                             ci_method = "eti",
                                              test = NULL,
                                              ...) {
   if ("iterations" %in% names(attributes(posteriors))) {
@@ -663,7 +663,7 @@ describe_posterior.emmGrid <- function(posteriors,
                                        centrality = "median",
                                        dispersion = FALSE,
                                        ci = 0.95,
-                                       ci_method = "hdi",
+                                       ci_method = "eti",
                                        test = c("p_direction", "rope"),
                                        rope_range = "default",
                                        rope_ci = 0.95,
@@ -724,7 +724,7 @@ describe_posterior.stanreg <- function(posteriors,
                                        centrality = "median",
                                        dispersion = FALSE,
                                        ci = 0.95,
-                                       ci_method = "hdi",
+                                       ci_method = "eti",
                                        test = c("p_direction", "rope"),
                                        rope_range = "default",
                                        rope_ci = 0.95,
@@ -794,7 +794,7 @@ describe_posterior.stanmvreg <- function(posteriors,
                                          centrality = "median",
                                          dispersion = FALSE,
                                          ci = 0.95,
-                                         ci_method = "hdi",
+                                         ci_method = "eti",
                                          test = "p_direction",
                                          rope_range = "default",
                                          rope_ci = 0.95,
@@ -859,7 +859,7 @@ describe_posterior.stanfit <- function(posteriors,
                                        centrality = "median",
                                        dispersion = FALSE,
                                        ci = 0.95,
-                                       ci_method = "hdi",
+                                       ci_method = "eti",
                                        test = c("p_direction", "rope"),
                                        rope_range = "default",
                                        rope_ci = 0.95,
@@ -912,7 +912,7 @@ describe_posterior.brmsfit <- function(posteriors,
                                        centrality = "median",
                                        dispersion = FALSE,
                                        ci = 0.95,
-                                       ci_method = "hdi",
+                                       ci_method = "eti",
                                        test = c("p_direction", "rope"),
                                        rope_range = "default",
                                        rope_ci = 0.95,
@@ -991,7 +991,7 @@ describe_posterior.MCMCglmm <- function(posteriors,
                                         centrality = "median",
                                         dispersion = FALSE,
                                         ci = 0.95,
-                                        ci_method = "hdi",
+                                        ci_method = "eti",
                                         test = c("p_direction", "rope"),
                                         rope_range = "default",
                                         rope_ci = 0.95,
@@ -1028,7 +1028,7 @@ describe_posterior.bcplm <- function(posteriors,
                                      centrality = "median",
                                      dispersion = FALSE,
                                      ci = 0.95,
-                                     ci_method = "hdi",
+                                     ci_method = "eti",
                                      test = c("p_direction", "rope"),
                                      rope_range = "default",
                                      rope_ci = 0.95,
@@ -1067,7 +1067,7 @@ describe_posterior.bamlss <- function(posteriors,
                                       centrality = "median",
                                       dispersion = FALSE,
                                       ci = 0.95,
-                                      ci_method = "hdi",
+                                      ci_method = "eti",
                                       test = c("p_direction", "rope"),
                                       rope_range = "default",
                                       rope_ci = 0.95,
@@ -1109,7 +1109,7 @@ describe_posterior.BFBayesFactor <- function(posteriors,
                                              centrality = "median",
                                              dispersion = FALSE,
                                              ci = 0.95,
-                                             ci_method = "hdi",
+                                             ci_method = "eti",
                                              test = c("p_direction", "rope", "bf"),
                                              rope_range = "default",
                                              rope_ci = 0.95,

diff --git a/R/rope.R b/R/rope.R
@@ -136,7 +136,7 @@ rope.default <- function(x, ...) {
 
 #' @rdname rope
 #' @export
-rope.numeric <- function(x, range = "default", ci = 0.95, ci_method = "HDI", verbose = TRUE, ...) {
+rope.numeric <- function(x, range = "default", ci = 0.95, ci_method = "ETI", verbose = TRUE, ...) {
   if (all(range == "default")) {
     range <- c(-0.1, 0.1)
   } else if (!all(is.numeric(range)) || length(range) != 2) {
@@ -173,7 +173,7 @@ rope.numeric <- function(x, range = "default", ci = 0.95, ci_method = "HDI", ver
 
 #' @rdname rope
 #' @export
-rope.data.frame <- function(x, range = "default", ci = 0.95, ci_method = "HDI", verbose = TRUE, ...) {
+rope.data.frame <- function(x, range = "default", ci = 0.95, ci_method = "ETI", verbose = TRUE, ...) {
   out <- .prepare_rope_df(x, range, ci, ci_method, verbose)
   HDI_area_attributes <- insight::compact_list(out$HDI_area)
   dat <- data.frame(
@@ -193,15 +193,15 @@ rope.data.frame <- function(x, range = "default", ci = 0.95, ci_method = "HDI",
 
 
 #' @export
-rope.draws <- function(x, range = "default", ci = 0.95, ci_method = "HDI", verbose = TRUE, ...) {
+rope.draws <- function(x, range = "default", ci = 0.95, ci_method = "ETI", verbose = TRUE, ...) {
   rope(.posterior_draws_to_df(x), range = range, ci = ci, ci_method = ci_method, verbose = verbose, ...)
 }
 
 
 
 #' @rdname rope
 #' @export
-rope.emmGrid <- function(x, range = "default", ci = 0.95, ci_method = "HDI", verbose = TRUE, ...) {
+rope.emmGrid <- function(x, range = "default", ci = 0.95, ci_method = "ETI", verbose = TRUE, ...) {
   xdf <- insight::get_parameters(x)
 
   dat <- rope(xdf, range = range, ci = ci, ci_method = ci_method, verbose = verbose, ...)
@@ -216,7 +216,7 @@ rope.emm_list <- rope.emmGrid
 
 #' @rdname rope
 #' @export
-rope.BFBayesFactor <- function(x, range = "default", ci = 0.95, ci_method = "HDI", verbose = TRUE, ...) {
+rope.BFBayesFactor <- function(x, range = "default", ci = 0.95, ci_method = "ETI", verbose = TRUE, ...) {
   if (all(range == "default")) {
     range <- rope_range(x, verbose = verbose)
   }
@@ -232,7 +232,7 @@ rope.bamlss <- rope.BFBayesFactor
 
 #' @rdname rope
 #' @export
-rope.MCMCglmm <- function(x, range = "default", ci = 0.95, ci_method = "HDI", verbose = TRUE, ...) {
+rope.MCMCglmm <- function(x, range = "default", ci = 0.95, ci_method = "ETI", verbose = TRUE, ...) {
   nF <- x$Fixed$nfl
   out <- rope(as.data.frame(x$Sol[, 1:nF, drop = FALSE]), range = range, ci = ci, ci_method = ci_method, verbose = verbose, ...)
   attr(out, "object_name") <- insight::safe_deparse(substitute(x))
@@ -241,7 +241,7 @@ rope.MCMCglmm <- function(x, range = "default", ci = 0.95, ci_method = "HDI", ve
 
 
 #' @export
-rope.mcmc <- function(x, range = "default", ci = 0.95, ci_method = "HDI", verbose = TRUE, ...) {
+rope.mcmc <- function(x, range = "default", ci = 0.95, ci_method = "ETI", verbose = TRUE, ...) {
   out <- rope(as.data.frame(x), range = range, ci = ci, ci_method = ci_method, verbose = verbose, ...)
   attr(out, "object_name") <- NULL
   attr(out, "data") <- insight::safe_deparse(substitute(x))
@@ -252,7 +252,7 @@ rope.mcmc <- function(x, range = "default", ci = 0.95, ci_method = "HDI", verbos
 
 
 #' @export
-rope.bcplm <- function(x, range = "default", ci = 0.95, ci_method = "HDI", verbose = TRUE, ...) {
+rope.bcplm <- function(x, range = "default", ci = 0.95, ci_method = "ETI", verbose = TRUE, ...) {
   out <- rope(insight::get_parameters(x), range = range, ci = ci, ci_method = ci_method, verbose = verbose, ...)
   attr(out, "object_name") <- NULL
   attr(out, "data") <- insight::safe_deparse(substitute(x))
@@ -274,7 +274,7 @@ rope.mcmc.list <- rope.bcplm
 
 
 #' @keywords internal
-.rope <- function(x, range = c(-0.1, 0.1), ci = 0.95, ci_method = "HDI", verbose = TRUE) {
+.rope <- function(x, range = c(-0.1, 0.1), ci = 0.95, ci_method = "ETI", verbose = TRUE) {
   ci_bounds <- ci(x, ci = ci, method = ci_method, verbose = verbose)
 
   if (anyNA(ci_bounds)) {
@@ -303,7 +303,7 @@ rope.mcmc.list <- rope.bcplm
 
 #' @rdname rope
 #' @export
-rope.stanreg <- function(x, range = "default", ci = 0.95, ci_method = "HDI", effects = c("fixed", "random", "all"), component = c("location", "all", "conditional", "smooth_terms", "sigma", "distributional", "auxiliary"), parameters = NULL, verbose = TRUE, ...) {
+rope.stanreg <- function(x, range = "default", ci = 0.95, ci_method = "ETI", effects = c("fixed", "random", "all"), component = c("location", "all", "conditional", "smooth_terms", "sigma", "distributional", "auxiliary"), parameters = NULL, verbose = TRUE, ...) {
   effects <- match.arg(effects)
   component <- match.arg(component)
 
@@ -346,7 +346,7 @@ rope.blavaan <- rope.stanreg
 rope.brmsfit <- function(x,
                          range = "default",
                          ci = 0.95,
-                         ci_method = "HDI",
+                         ci_method = "ETI",
                          effects = c("fixed", "random", "all"),
                          component = c("conditional", "zi", "zero_inflated", "all"),
                          parameters = NULL,
@@ -427,7 +427,7 @@ rope.brmsfit <- function(x,
 
 
 #' @export
-rope.sim.merMod <- function(x, range = "default", ci = 0.95, ci_method = "HDI", effects = c("fixed", "random", "all"), parameters = NULL, verbose = TRUE, ...) {
+rope.sim.merMod <- function(x, range = "default", ci = 0.95, ci_method = "ETI", effects = c("fixed", "random", "all"), parameters = NULL, verbose = TRUE, ...) {
   effects <- match.arg(effects)
 
   if (all(range == "default")) {
@@ -490,7 +490,7 @@ rope.sim.merMod <- function(x, range = "default", ci = 0.95, ci_method = "HDI",
 
 
 #' @export
-rope.sim <- function(x, range = "default", ci = 0.95, ci_method = "HDI", parameters = NULL, verbose = TRUE, ...) {
+rope.sim <- function(x, range = "default", ci = 0.95, ci_method = "ETI", parameters = NULL, verbose = TRUE, ...) {
   if (all(range == "default")) {
     range <- rope_range(x, verbose = verbose)
   } else if (!all(is.numeric(range)) || length(range) != 2) {

diff --git a/R/sexit.R b/R/sexit.R
@@ -135,7 +135,7 @@ sexit <- function(x, significant = "default", large = "default", ci = 0.95, ...)
   centrality$Effects <- centrality$Component <- NULL
   centrality_text <- paste0("Median = ", insight::format_value(centrality$Median))
   direction <- ifelse(centrality$Median < 0, "negative", "positive")
-  uncertainty <- ci(x, ci = ci, method = "HDI", ...)[c("CI", "CI_low", "CI_high")]
+  uncertainty <- ci(x, ci = ci, method = "ETI", ...)[c("CI", "CI_low", "CI_high")]
   uncertainty_text <- insight::format_ci(uncertainty$CI_low, uncertainty$CI_high, uncertainty$CI)
 
   # Indices
@@ -216,7 +216,7 @@ sexit <- function(x, significant = "default", large = "default", ci = 0.95, ...)
 
   # Prepare output
   attr(out, "sexit_info") <- "Following the Sequential Effect eXistence and sIgnificance Testing (SEXIT) framework, we report the median of the posterior distribution and its 95% CI (Highest Density Interval), along the probability of direction (pd), the probability of significance and the probability of being large."
-  attr(out, "sexit_ci_method") <- "HDI"
+  attr(out, "sexit_ci_method") <- "ETI"
   attr(out, "sexit_significance") <- significant
   attr(out, "sexit_large") <- large
   attr(out, "sexit_textlong") <- text_full