update to roxygen2 v7.0.1

Author: jgabry

.travis.yml

@@ -6,10 +6,13 @@ cache: packages
 
 r_github_packages:
   - r-lib/covr
-  - tidyverse/ggplot2
 
 r_build_args: '--no-build-vignettes'
 r_check_args: '--ignore-vignettes'
+warnings_are_errors: true
+
+env:
+- _R_CHECK_FORCE_SUGGESTS_=false NOT_CRAN=true MAKEFLAGS=-j2
 
 before_install:
   - mkdir -p ~/.R

DESCRIPTION

@@ -49,7 +49,7 @@ Suggests:
     shinystan (>= 2.3.0),
     testthat (>= 2.0.0),
     vdiffr
-RoxygenNote: 6.1.1
+RoxygenNote: 7.0.1
 VignetteBuilder: knitr
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)

R/bayesplot-package.R

@@ -19,7 +19,7 @@
 #' only to provide convenient functionality for users, but also a common set of
 #' functions that can be easily used by developers working on a variety of
 #' packages for Bayesian modeling, particularly (but not necessarily) packages
-#' powered by [**rstan**][rstan::rstan-package] (the \R interface to Stan).
+#' powered by RStan (the \R interface to Stan).
 #' Examples of packages that will soon (or already are) using **bayesplot** are
 #' **rstan** itself, as well as the **rstan**-dependent **rstanarm** and
 #' **brms** packages for applied regression modeling.
@@ -32,11 +32,11 @@
 #'  }
 #'
 #' The plotting functions in **bayesplot** are organized into several modules:
-#' * [__MCMC__][MCMC-overview]: Visualizations of Markov chain
+#' * [MCMC][MCMC-overview]: Visualizations of Markov chain
 #'   Monte Carlo (MCMC) simulations generated by *any* MCMC algorithm
 #'   as well as diagnostics. There are also additional functions specifically
 #'   for use with models fit using the [No-U-Turn Sampler (NUTS)][NUTS].
-#' * [__PPC__][PPC-overview]: Graphical prior and posterior predictive
+#' * [PPC][PPC-overview]: Graphical prior and posterior predictive
 #'   checks (PPCs).
 #'
 #' In future releases modules will be added specifically for

R/helpers-mcmc.R

@@ -310,6 +310,9 @@ parameter_names.array <- function(x) {
 parameter_names.default <- function(x) {
   colnames(x) %||% abort("No parameter names found.")
 }
+# parameter_names.matrix <- function(x) {
+#   colnames(x) %||% abort("No parameter names found.")
+# }
 
 # Check if an object is a 3-D array
 is_3d_array <- function(x) {

R/mcmc-intervals.R

@@ -13,9 +13,9 @@
 #' @param ... Currently unused.
 #' @param prob The probability mass to include in the inner interval (for
 #'   `mcmc_intervals()`) or in the shaded region (for `mcmc_areas()`). The
-#'   default is `0.5` (50\% interval) and `1` for `mcmc_areas_ridges()`.
+#'   default is `0.5` (50% interval) and `1` for `mcmc_areas_ridges()`.
 #' @param prob_outer The probability mass to include in the outer interval. The
-#'   default is `0.9` for `mcmc_intervals()` (90\% interval) and
+#'   default is `0.9` for `mcmc_intervals()` (90% interval) and
 #'   `1` for `mcmc_areas()` and for `mcmc_areas_ridges()`.
 #' @param area_method How to constrain the areas in `mcmc_areas()`. The
 #'   default is `"equal area"`, setting the density curves to have the same

R/mcmc-overview.R

@@ -11,46 +11,47 @@
 #' documentation for various categories of MCMC plots. Currently the MCMC
 #' plotting functions accept posterior draws provided in one of the following
 #' formats:
-#' * __3-D array__: An array with dimensions `[Iteration, Chain, Parameter]`
-#'   in that order.
+#' * __3-D array__: An array with dimensions `Iteration, Chain, Parameter` in
+#' that order.
 #' * __list__: A list of matrices, where each matrix corresponds to a Markov
-#'   chain. All of the matrices should have the same number of iterations (rows)
-#'   and parameters (columns), and parameters should have the same names and be
-#'   in the same order.
+#' chain. All of the matrices should have the same number of iterations (rows)
+#' and parameters (columns), and parameters should have the same names and be in
+#' the same order.
 #' * __matrix (2-D array)__: A matrix with one column per parameter. If using
-#'   matrix there should only be a single Markov chain or all chains should
-#'   already be merged (stacked).
-#' * __data frame__: There are two types of [data frames][base::data.frame]
-#'   allowed. Either a data frame with one column per parameter (if only a single
-#'   chain or all chains have already been merged), or a data frame with one
-#'   column per parameter plus an additional column `"Chain"` that contains the
-#'   chain number (an integer) corresponding to each row in the data frame.
+#' matrix there should only be a single Markov chain or all chains should
+#' already be merged (stacked).
+#' * __data frame__: There are two types of data frames allowed. Either a data
+#' frame with one column per parameter (if only a single chain or all chains
+#' have already been merged), or a data frame with one column per parameter plus
+#' an additional column `"Chain"` that contains the chain number (an integer)
+#' corresponding to each row in the data frame.
 #'
 #' __Note__: typically the user should *not* include warmup iterations
 #' in the object passed to **bayesplot** plotting functions, although for
 #' certain plots (e.g. trace plots) it can occasionally be useful to include the
 #' warmup iterations for diagnostic purposes.
 #'
 #' @section MCMC plotting functions:
-#' * [__Posterior distributions__][MCMC-distributions]:
+#'
+#' * [Posterior distributions][MCMC-distributions]:
 #'   Histograms and kernel density plots of parameter draws, optionally
 #'   showing each Markov chain separately.
-#' * [__Uncertainty intervals__][MCMC-intervals]: Uncertainty intervals computed
+#' * [Uncertainty intervals][MCMC-intervals]: Uncertainty intervals computed
 #'   from parameter draws.
-#' * [__Trace plots__][MCMC-traces]: Times series of parameter draws, optionally
+#' * [Trace plots][MCMC-traces]: Times series of parameter draws, optionally
 #'   including HMC/NUTS diagnostic information.
-#' * [__Scatterplots__][MCMC-scatterplots]: Scatterplots, heatmaps, and pairs
+#' * [Scatterplots][MCMC-scatterplots]: Scatterplots, heatmaps, and pairs
 #'   plots of parameter draws, optionally including HMC/NUTS diagnostic
 #'   information.
-#' * [__Parallel coordinates plots__][MCMC-parcoord]: Parallel coordinates plot
+#' * [Parallel coordinates plots][MCMC-parcoord]: Parallel coordinates plot
 #'   of MCMC draws (one dimension per parameter), optionally including
 #'   HMC/NUTS diagnostic information.
-#' * [__Combos__][MCMC-combos]: Combination plots (e.g. trace plot + histogram).
-#' * [__General MCMC diagnostics__][MCMC-diagnostics]: MCMC diagnostic plots
+#' * [Combos][MCMC-combos]: Combination plots (e.g. trace plot + histogram).
+#' * [General MCMC diagnostics][MCMC-diagnostics]: MCMC diagnostic plots
 #'   including R-hat, effective sample size, autocorrelation.
-#'   [__NUTS diagnostics__][MCMC-nuts]: Special diagnostic plots for
+#'   [NUTS diagnostics][MCMC-nuts]: Special diagnostic plots for
 #'     the No-U-Turn Sampler.
-#' * [__Comparisons to "true" values__][MCMC-recover]: Plots comparing MCMC
+#' * [Comparisons to "true" values][MCMC-recover]: Plots comparing MCMC
 #'     estimates to "true" parameter values (e.g., values used to simulate data).
 #'
 #' @template reference-vis-paper

R/mcmc-recover.R

@@ -27,9 +27,9 @@
 #'   within which it makes sense to use the same y-axis.
 #' @param ... Currently unused.
 #' @param prob The probability mass to include in the inner interval. The
-#'   default is `0.5` (50\% interval).
+#'   default is `0.5` (50% interval).
 #' @param prob_outer The probability mass to include in the outer interval. The
-#'   default is `0.9` (90\% interval).
+#'   default is `0.9` (90% interval).
 #' @param point_est The point estimate to show. Either `"median"` (the
 #'   default), `"mean"`, or `"none"`.
 #' @param size,alpha Passed to [ggplot2::geom_point()] to control the

R/ppc-loo.R

@@ -284,7 +284,7 @@ ppc_loo_pit <-
 #'   are computed internally before plotting. If specified, `intervals`
 #'   must be a matrix with number of rows equal to the number of data points and
 #'   five columns in the following order: lower outer interval, lower inner
-#'   interval, median (50\%), upper inner interval and upper outer interval
+#'   interval, median (50%), upper inner interval and upper outer interval
 #'   (column names are ignored).
 #' @param order For `ppc_loo_intervals()`, a string indicating how to arrange
 #'   the plotted intervals. The default (`"index"`) is to plot them in the