Update to mice 3.16.17

DESCRIPTION

@@ -1,8 +1,8 @@
 Package: mice
 Type: Package
-Version: 3.16.16
+Version: 3.16.17
 Title: Multivariate Imputation by Chained Equations
-Date: 2024-10-16
+Date: 2024-11-22
 Authors@R: c(person("Stef", "van Buuren", role = c("aut","cre"),
     email = "[email protected]"),
     person("Karin", "Groothuis-Oudshoorn", role = "aut",

NEWS.md

@@ -1,3 +1,7 @@
+# mice 3.16.17
+
+* Create version to perform reverse dependency checks
+
 # mice 3.16.16
 
 * Prevent `as.mids()` from filling the `imp` object for complete variables

R/ampute.R

@@ -40,8 +40,6 @@
 #' mechanisms: the missingness depends completely on chance (MCAR), the missingness
 #' depends on the values of the observed variables (i.e. the variables that remain
 #' complete) (MAR) or on the values of the variables that will be made incomplete (MNAR).
-#' For a discussion on how missingness mechanisms are related to the observed data,
-#' we refer to \doi{10.1177/0049124118799376}.
 #'
 #' When the user specifies the missingness mechanism to be \code{"MCAR"}, the candidates
 #' have an equal probability of becoming incomplete. For a \code{"MAR"} or \code{"MNAR"} mechanism,
@@ -82,11 +80,9 @@
 #' The continuous distributions of probabilities are based on the logistic distribution function.
 #' The user can specify the type of missingness, which, again, may differ between patterns.
 #'
-#' For an example and more explanation about how the arguments interact with each other,
-#' we refer to the vignette
-#' \href{https://rianneschouten.github.io/mice_ampute/vignette/ampute.html}{Generate missing values with ampute}
-#' The amputation methodology is published in
-#' \doi{10.1080/00949655.2018.1491577}
+#' For an example and more explanation about how the arguments interact with
+#' each other, we refer to the vignette:
+#' \href{https://rianneschouten.github.io/mice_ampute/vignette/ampute.html}{Generate missing values with ampute}.
 #'
 #' @param data A complete data matrix or data frame. Values should be numeric.
 #' Categorical variables should have been transformed to dummies.
@@ -156,7 +152,8 @@
 #' @seealso \code{\link{mads-class}}, \code{\link{bwplot}}, \code{\link{xyplot}},
 #' \code{\link{mice}}
 #'
-#' @references Brand, J.P.L. (1999) \emph{Development, implementation and
+#' @references
+#' Brand, J.P.L. (1999) \emph{Development, implementation and
 #' evaluation of multiple imputation strategies for the statistical analysis of
 #' incomplete data sets.} pp. 110-113. Dissertation. Rotterdam: Erasmus University.
 #'

revdep/check.R

@@ -12,19 +12,19 @@ library(revdepcheck)
 revdep_reset()
 
 # the following takes two hours
-revdep_check(num_workers = 3)
+revdep_check(num_workers = 10)
 
 # print out results
 revdep_summary()
 revdep_details(revdep = "smartdata")
 
-# commit 
+# commit
 system("git add revdep/*.md")
 system("git commit -m 'Update revdep results'")
 system("git push -u origin HEAD")
 
 # signal package authors
 
 
-# after successfully submitted to CRAN, clean up 
+# after successfully submitted to CRAN, clean up
 revdep_reset()