fix Rds

R/plot_coefs.R

@@ -9,7 +9,7 @@
 #' @import ggplot2
 #' @import bayesplot
 #' @param object An output from [walker()].
-#' @param level Level for intervals. Default is 0.05, leading to 90\% intervals.
+#' @param level Level for intervals. Default is 0.05, leading to 90% intervals.
 #' @param alpha Transparency level for [ggplot2::geom_ribbon()].
 #' @param transform Optional vectorized function for transforming the coefficients (for example `exp`).
 #' @param scales Should y-axis of the panels be `"fixed"` (default) or `"free"`?

R/plot_fit.R

@@ -1,7 +1,7 @@
 #' Plot the fitted values and sample quantiles for a walker object
 #' 
 #' @param object An output from [walker()] or [walker_glm()].
-#' @param level Level for intervals. Default is 0.05, leading to 90\% intervals.
+#' @param level Level for intervals. Default is 0.05, leading to 90% intervals.
 #' @param alpha Transparency level for [ggplot2::geom_ribbon()].
 #' @param ... Further arguments to [bayesplot::ppc_ribbon()].
 #' @export
@@ -18,4 +18,4 @@ plot_fit <- function(object, level = 0.05, alpha = 0.33, ...){
     x = as.numeric(time(object$y))[noNA], ...) + 
     theme(legend.position = "none") + 
     scale_x_continuous(name = "time")
-}
+}

R/plot_predict.R

@@ -9,7 +9,7 @@
 #' @param draw_obs Either `"response"`, `"mean"`, or `"none"`, 
 #' where `"mean"` is response variable divided by number of trials or exposures 
 #' in case of binomial/poisson models. 
-#' @param level Level for intervals. Default is 0.05, leading to 90\% intervals.
+#' @param level Level for intervals. Default is 0.05, leading to 90% intervals.
 #' @param alpha Transparency level for [ggplot2::geom_ribbon()].
 #' @export
 #' @examples