easystats · strengejacke · Oct 24, 2023 · Oct 12, 2023 · Oct 12, 2023 · Oct 13, 2023
diff --git a/DESCRIPTION b/DESCRIPTION
@@ -117,4 +117,4 @@ Config/Needs/website:
     rstudio/bslib,
     r-lib/pkgdown,
     easystats/easystatstemplate
-Remotes: easystats/insight, easystats/bayestestR
+Remotes: easystats/bayestestR
diff --git a/R/plot.hdi.R b/R/plot.hdi.R
@@ -32,7 +32,7 @@
    plot_title <- "Credible Interval (CI)"
  }

  if (!is.null(parms)) {
    params <- parms
  } else {
    params <- NULL
@@ -59,13 +59,13 @@
    data <- data[levels_order]
    dataplot <- data.frame()
    for (i in names(data)) {
      if (!is.null(params)) {
        dataplot <- rbind(
          dataplot,
          cbind(
            .compute_densities_hdi(data[[i]], hdi = as.data.frame(x[x$Parameter == i, ]), name = i),
            "Effects" = params$Effects[params$Parameter == i],
            "Component" = params$Component[params$Parameter == i]
          )
        )
      } else {
@@ -140,8 +140,8 @@

  out <- .as.data.frame_density(stats::density(x))

  out$HDI_low <- sapply(out$x, .classify_hdi, hdi$CI_low, c(100, 100 * hdi$CI))
  out$HDI_high <- sapply(out$x, .classify_hdi, rev(hdi$CI_high), c(rev(100 * hdi$CI), 100))
  out$fill <- as.factor(pmax(out$HDI_low, out$HDI_high))
  out$height <- out$y
  out$y <- name
@@ -149,7 +149,7 @@
  levels(out$fill) <- sprintf("%s%%", levels(out$fill))

  # normalize
  out$height <- as.vector((out$height - min(out$height, na.rm = TRUE)) / diff(range(out$height, na.rm = TRUE), na.rm = TRUE))

  out
 }
@@ -199,7 +199,7 @@
 #' library(bayestestR)
 #' set.seed(123)
 #' m <- suppressWarnings(stan_glm(Sepal.Length ~ Petal.Width * Species, data = iris, refresh = 0))
-#' result <- hdi(m)
+#' result <- bayestestR::hdi(m)
 #' result
 #' plot(result)
 #'

diff --git a/R/plot.parameters_brms_meta.R b/R/plot.parameters_brms_meta.R
@@ -59,9 +59,9 @@

  attr(dataplot, "summary") <- summary
  attr(dataplot, "info") <- list(
    "xlab" = "Standardized Mean Difference",
    "ylab" = NULL,
    "legend_fill" = NULL,
    "legend_color" = NULL,
    "title" = "Bayesian Meta-Analysis"
  )
@@ -129,7 +129,9 @@
 #'   prior(normal(0, 1), class = Intercept),
 #'   prior(cauchy(0, 0.5), class = sd)
 #' )
-#' model <- brm(yi | se(vi) ~ 1 + (1 | author), data = dat)
+#' model <- suppressWarnings(
+#'   brm(yi | se(vi) ~ 1 + (1 | author), data = dat)
+#' )
 #'
 #' # result
 #' mp <- model_parameters(model)

diff --git a/R/plot.parameters_model.R b/R/plot.parameters_model.R
@@ -513,7 +513,9 @@ plot.see_parameters_model <- function(x,
   } else if (has_response) {
     p <- p + facet_wrap(~Response, ncol = n_columns, scales = facet_scales)
   } else if (has_subgroups) {
-    suppressWarnings(p <- p + facet_grid(Subgroup ~ ., scales = "free", space = "free")) # nolint
+    suppressWarnings({
+      p <- p + facet_grid(Subgroup ~ ., scales = "free", space = "free")
+    })
   }
 
   if (length(model_attributes$parameter_names) > 1L) {

diff --git a/R/plot.parameters_pca.R b/R/plot.parameters_pca.R
@@ -33,6 +33,8 @@ data_plot.parameters_pca <- function(x, data = NULL, ...) {
     title <- paste0("Rotated loadings from ", title, " (", rotation_name, ")")
   }
 
+  # remove missing values in y, to avoid warning
+  dataplot <- dataplot[!is.na(dataplot$y), ]
 
   attr(dataplot, "info") <- list(
     "xlab" = "",

diff --git a/R/plot.si.R b/R/plot.si.R
@@ -17,7 +17,7 @@
 #' library(bayestestR)
 #' set.seed(123)
 #' m <<- suppressWarnings(stan_glm(Sepal.Length ~ Petal.Width * Species, data = iris, refresh = 0))
-#' result <- si(m)
+#' result <- si(m, verbose = FALSE)
 #' result
 #' plot(result)
 #'

diff --git a/R/plot.visualisation_recipe.R b/R/plot.visualisation_recipe.R
@@ -5,11 +5,10 @@ plot.see_visualisation_recipe <- function(x, ...) {
     if (!"ggraph" %in% .packages()) {
       attachNamespace("ggraph") # Needs to be attached
     }
-    ggraph::ggraph(attributes(x)$data, layout = attributes(x)$layout) +
-      geoms_from_list(x)
+    suppressWarnings(ggraph::ggraph(attributes(x)$data, layout = attributes(x)$layout) + geoms_from_list(x))
   } else {
-    ggplot2::ggplot(data = attributes(x)$data) +
-      geoms_from_list(x, ...)
+    suppressWarnings(ggplot2::ggplot(data = attributes(x)$data) +
+      geoms_from_list(x, ...))
   }
 }
 
@@ -23,7 +22,7 @@ plot.see_visualisation_recipe <- function(x, ...) {
 plot.see_visualisation_recipes <- function(x, ...) {
   the_plots <- list()
   for (i in names(x)) {
-    the_plots[[i]] <- graphics::plot(x[[i]])
+    the_plots[[i]] <- suppressWarnings(graphics::plot(x[[i]]))
   }
   pw <- plots(the_plots, ...)
   .safe_print_plots(pw)

diff --git a/R/print.check_model.R b/R/print.check_model.R
@@ -9,13 +9,13 @@ print.see_check_model <- function(x,
   # to plot(), "type" is no longer recognized as "missing()"
   plot_type <- attr(x, "type")
 
-  if (missing(type) && !is.null(plot_type) && plot_type %in% c("density", "discrete_dots", "discrete_interval", "discrete_both")) {
+  if (missing(type) && !is.null(plot_type) && plot_type %in% c("density", "discrete_dots", "discrete_interval", "discrete_both")) { # nolint
     type <- plot_type
   } else {
     type <- match.arg(type, choices = c("density", "discrete_dots", "discrete_interval", "discrete_both"))
   }
 
-  suppressWarnings(suppressMessages(plot(
+  suppressWarnings(suppressMessages(graphics::plot(
     x,
     style = style,
     colors = colors,

diff --git a/R/utils.R b/R/utils.R
@@ -7,10 +7,12 @@
   return(x)
 }
 
+
 .as.data.frame_density <- function(x, ...) {
   data.frame(x = x$x, y = x$y)
 }
 
+
 # safe conversion from factor to numeric
 .factor_to_numeric <- function(x) {
   if (is.numeric(x)) {
@@ -27,11 +29,13 @@
   as.numeric(as.character(x))
 }
 
+
 .has_multiple_panels <- function(x) {
   (!"Effects" %in% names(x) || insight::n_unique(x$Effects) <= 1L) &&
     (!"Component" %in% names(x) || insight::n_unique(x$Component) <= 1L)
 }
 
+
 .clean_parameter_names <- function(params, grid = FALSE) {
   params <- unique(params)
   labels <- params
@@ -90,7 +94,6 @@
 }
 
 
-
 .fix_facet_names <- function(x) {
   if ("Component" %in% names(x)) {
     x$Component <- as.character(x$Component)
@@ -117,7 +120,6 @@
 }
 
 
-
 .intercept_names <-
   c(
     "(intercept)_zi",

diff --git a/man/plot.see_hdi.Rd b/man/plot.see_hdi.Rd
diff --git a/man/plot.see_parameters_brms_meta.Rd b/man/plot.see_parameters_brms_meta.Rd
diff --git a/man/plot.see_si.Rd b/man/plot.see_si.Rd
diff --git a/vignettes/bayestestR.Rmd b/vignettes/bayestestR.Rmd
@@ -361,7 +361,7 @@ represent the density of the null at the value - the ratio of their heights is
 the value of the Savage-Dickey Bayes factor:
 
 ```{r}
-result <- bayesfactor_parameters(model)
+result <- bayesfactor_parameters(model, verbose = FALSE)
 
 result
 

diff --git a/vignettes/modelbased.Rmd b/vignettes/modelbased.Rmd
@@ -122,12 +122,18 @@ plot(result)
 ```
 
 
-```{r slopes-poly}
+```{r slopes-poly, echo=TRUE, eval=FALSE}
 model <- lm(Petal.Length ~ Species * poly(Sepal.Width, 3), data = iris)
 
 result <- estimate_slopes(model, at = c("Sepal.Width", "Species"))
 plot(result)
 ```
+```{r slopes-poly2, eval=can_evaluate, echo=FALSE}
+model <- lm(Petal.Length ~ Species * poly(Sepal.Width, 3), data = iris)
+
+result <- estimate_slopes(model, at = c("Sepal.Width", "Species"))
+suppressWarnings(print(plot(result)))
+```
 
 # Estimate derivatives
 

diff --git a/vignettes/parameters.Rmd b/vignettes/parameters.Rmd
@@ -190,7 +190,7 @@ density estimation plots [from Bayesian
 models](https://easystats.github.io/see/articles/bayestestR.html).
 
 ```{r}
-result <- simulate_parameters(model1)
+result <<- simulate_parameters(model1)
 
 plot(result)
 ```
@@ -245,7 +245,12 @@ estimations](https://easystats.github.io/see/articles/bayestestR.html)).
 #   family = zero_inflated_poisson()
 # )
 brms_model <- insight::download_model("brms_zi_2")
-result <- model_parameters(brms_model, effects = "all", component = "all")
+result <- model_parameters(
+  brms_model,
+  effects = "all",
+  component = "all",
+  verbose = FALSE
+)
 
 plot(result)
 ```
@@ -255,7 +260,9 @@ plot(result)
 ```{r}
 result <- model_parameters(brms_model,
   effects = "all",
-  component = "all", group_level = TRUE
+  component = "all",
+  group_level = TRUE,
+  verbose = FALSE
 )
 plot(result)
 ```