leeper · bbolker · Apr 16, 2024 · Apr 16, 2024 · Jun 10, 2024 · Jun 10, 2024
diff --git a/.aspell/defaults.R b/.aspell/defaults.R
@@ -0,0 +1,4 @@
+Rd_files <- vignettes <- R_files <- description <-
+    list(encoding = "UTF-8",
+         language = "en",
+         dictionaries = c("en_stats", "mydict"))
diff --git a/.aspell/mydict.rds b/.aspell/mydict.rds
diff --git a/.gitignore b/.gitignore
@@ -15,3 +15,5 @@ README.html
 /vignettes/figure/
 /vignettes/*.bib.bak
 /revdep/
+\#*
+.#*
diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,22 +1,21 @@
 Package: prediction
 Type: Package
 Title: Tidy, Type-Safe 'prediction()' Methods
-Description: A one-function package containing 'prediction()', a type-safe alternative to 'predict()' that always returns a data frame. The 'summary()' method provides a data frame with average predictions, possibly over counterfactual versions of the data (a la the 'margins' command in 'Stata'). Marginal effect estimation is provided by the related package, 'margins' <https://cran.r-project.org/package=margins>. The package currently supports common model types (e.g., "lm", "glm") from the 'stats' package, as well as numerous other model classes from other add-on packages. See the README or main package documentation page for a complete listing.
+Description: A one-function package containing prediction(), a type-safe alternative to predict() that always returns a data frame. The summary() method provides a data frame with average predictions, possibly over counterfactual versions of the data (à la the margins command in 'Stata'). Marginal effect estimation is provided by the related package, 'margins' <https://cran.r-project.org/package=margins>. The package currently supports common model types (e.g., lm, glm) from the 'stats' package, as well as numerous other model classes from other add-on packages. See the README file or main package documentation page for a complete listing.
 License: MIT + file LICENSE
-Version: 0.3.15
-Date: 2019-12-24
+Version: 0.3.18
 Authors@R: c(person("Thomas J.", "Leeper",
-                    role = c("aut", "cre"), 
-                    email = "thosjleeper@gmail.com",
+                    role = c("aut"), 
                     comment = c(ORCID = "0000-0003-4097-6326")),
-             person("Carl", "Ganz", role = "ctb",
-                    email = "carlganz@ucla.edu"),
+             person("Carl", "Ganz", role = "ctb"),
              person("Vincent", "Arel-Bundock", role = "ctb",
-                    email = "vincent.arel-bundock@umontreal.ca",
-                    comment = c(ORCID = "0000-0003-2042-7063"))
+                    comment = c(ORCID = "0000-0003-2042-7063")),
+             person("Ben","Bolker",email="bolker@mcmaster.ca", 
+                    role=c("ctb","cre"),
+                    comment=c(ORCID="0000-0002-2127-0443"))
             )
-URL: https://github.com/leeper/prediction
-BugReports: https://github.com/leeper/prediction/issues
+URL: https://github.com/bbolker/prediction
+BugReports: https://github.com/bbolker/prediction/issues
 Depends: R (>= 3.5.0)
 Imports:
     utils,
@@ -37,7 +36,6 @@ Enhances:
     e1071,
     earth,
     ff,
-    ffbase,
     gam (>= 1.15),
     gee,
     glmnet,
@@ -64,4 +62,4 @@ Enhances:
     VGAM
 ByteCompile: true
 Encoding: UTF-8
-RoxygenNote: 7.0.2
+RoxygenNote: 7.3.2
diff --git a/NAMESPACE b/NAMESPACE
@@ -4,6 +4,7 @@ S3method(find_data,crch)
 S3method(find_data,data.frame)
 S3method(find_data,default)
 S3method(find_data,glimML)
+S3method(find_data,glimQL)
 S3method(find_data,glm)
 S3method(find_data,hxlr)
 S3method(find_data,lm)
@@ -25,6 +26,8 @@ S3method(prediction,Gam)
 S3method(prediction,ar)
 S3method(prediction,arima0)
 S3method(prediction,betareg)
+S3method(prediction,bigLm)
+S3method(prediction,bigglm)
 S3method(prediction,biglm)
 S3method(prediction,bruto)
 S3method(prediction,clm)
@@ -48,6 +51,7 @@ S3method(prediction,ivreg)
 S3method(prediction,knnreg)
 S3method(prediction,kqr)
 S3method(prediction,ksvm)
+S3method(prediction,lda)
 S3method(prediction,lm)
 S3method(prediction,lme)
 S3method(prediction,loess)
@@ -56,15 +60,19 @@ S3method(prediction,mars)
 S3method(prediction,mca)
 S3method(prediction,mclogit)
 S3method(prediction,merMod)
+S3method(prediction,mlogit)
+S3method(prediction,mnlogit)
 S3method(prediction,mnp)
 S3method(prediction,multinom)
+S3method(prediction,naiveBayes)
 S3method(prediction,nls)
 S3method(prediction,nnet)
 S3method(prediction,plm)
 S3method(prediction,polr)
 S3method(prediction,polyreg)
 S3method(prediction,ppr)
 S3method(prediction,princomp)
+S3method(prediction,qda)
 S3method(prediction,rlm)
 S3method(prediction,rpart)
 S3method(prediction,rq)
@@ -75,7 +83,10 @@ S3method(prediction,survreg)
 S3method(prediction,svm)
 S3method(prediction,svyglm)
 S3method(prediction,train)
+S3method(prediction,tree)
 S3method(prediction,truncreg)
+S3method(prediction,vgam)
+S3method(prediction,vglm)
 S3method(prediction,zeroinfl)
 S3method(print,prediction)
 S3method(print,summary.prediction)

diff --git a/NEWS.md b/NEWS.md
@@ -1,3 +1,8 @@
+## prediction 0.3.18
+
+* under new maintainership
+* various cosmetic/CRAN check updates
+
 ## prediction 0.3.15
 
 * `build_datalist()` now works correctly with data.table datasets. (#34, #35, h/t Dan Schrage)

diff --git a/R/find_data.R b/R/find_data.R
@@ -73,6 +73,8 @@ find_data.glimML <- function(model, ...) {
     methods::slot(model, "data")
 }
 
+#' @rdname find_data
+#' @export
 find_data.glimQL <- function(model, env = parent.frame(), ...) {
     requireNamespace("methods", quietly = TRUE)
     methods::slot(model, "fm")$data

diff --git a/R/margex.R b/R/margex.R
@@ -16,7 +16,8 @@
 #'    \item{\samp{agegroup}}{A factor with three levels}
 #'    \item{\samp{arm}}{A factor with three levels}
 #'  }
-#' @source \url{http://www.stata-press.com/data/r14/margex.dta}
+#' @source \url{https://www.stata-press.com/data/r14/margex.dta}
+#' @usage data("margex")
 #' @examples
 #' \donttest{
 #' 

diff --git a/R/prediction.R b/R/prediction.R
@@ -19,7 +19,7 @@
 #'   \item \dQuote{ar}, see \code{\link[stats]{ar}}
 #'   \item \dQuote{Arima}, see \code{\link[stats]{arima}}
 #'   \item \dQuote{arima0}, see \code{\link[stats]{arima0}}
-#'   \item \dQuote{bigglm}, see \code{\link[biglm]{bigglm}} (including \dQuote{ffdf}-backed models provided by \code{\link[ffbase]{bigglm.ffdf}})
+#'   \item \dQuote{bigglm}, see \code{\link[biglm]{bigglm}}
 #'   \item \dQuote{betareg}, see \code{\link[betareg]{betareg}}
 #'   \item \dQuote{bruto}, see \code{\link[mda]{bruto}}
 #'   \item \dQuote{clm}, see \code{\link[ordinal]{clm}}
@@ -75,7 +75,7 @@
 #'   \item \dQuote{zeroinfl}, see \code{\link[pscl]{zeroinfl}}
 #' }
 #' 
-#' Where implemented, \code{prediction} also returns average predictions (and the variances thereof). Variances are implemented using the delta method, as described in \url{http://indiana.edu/~jslsoc/stata/ci_computations/spost_deltaci.pdf}.
+#' Where implemented, \code{prediction} also returns average predictions (and the variances thereof). Variances are implemented using the delta method, as described by Xu and Long 2005 \doi{10.1177/1536867X0500500405}.
 #' 
 #' @return A data frame with class \dQuote{prediction} that has a number of rows equal to number of rows in \code{data}, or a multiple thereof, if \code{!is.null(at)}. The return value contains \code{data} (possibly modified by \code{at} using \code{\link{build_datalist}}), plus a column containing fitted/predicted values (\code{"fitted"}) and a column containing the standard errors thereof (\code{"calculate_se"}). Additional columns may be reported depending on the object class. The data frame also carries attributes used by \code{print} and \code{summary}, which will be lost during subsetting.
 #' @examples
@@ -97,14 +97,21 @@
 #' prediction(x, at = lapply(iris, mean_or_mode))
 #' 
 #' # prediction with multi-category outcome
-#' \dontrun{
-#'   library("mlogit")
-#'   data("Fishing", package = "mlogit")
-#'   Fish <- mlogit.data(Fishing, varying = c(2:9), shape = "wide", choice = "mode")
-#'   mod <- mlogit(mode ~ price + catch, data = Fish)
-#'   prediction(mod)
-#'   prediction(mod, category = 3)
+#' if (requireNamespace("mlogit")) {
+#'     data("Fishing", package = "mlogit")
+#'     Fish <- mlogit.data(Fishing, varying = c(2:9), shape = "wide", choice = "mode")
+#'     mod <- mlogit(mode ~ price + catch, data = Fish)
+#'     prediction(mod)
+#'     prediction(mod, category = 3)
 #' }
+#'
+#' # standard errors of predictions for GLMs
+#' m1 <- glm(breaks ~ wool * tension, data = warpbreaks, family = poisson)
+#' p1 <- prediction(m1,
+#'      at = with(warpbreaks,
+#'                  list(wool = levels(wool), tension= levels(tension))))
+#' ss <- summary(p1)
+#' print(ss)
 #' 
 #' @keywords models
 #' @seealso \code{\link{find_data}}, \code{\link{build_datalist}}, \code{\link{mean_or_mode}}, \code{\link{seq_range}}

diff --git a/R/prediction_bigFastLm.R b/R/prediction_bigFastLm.R
@@ -1,5 +1,5 @@
-# @rdname prediction
-# @export
+#' @rdname prediction
+#' @export
 prediction.bigLm <- 
 function(model, 
          data = NULL,
@@ -35,4 +35,4 @@ function(model,
               vcov = vc,
               jacobian = NULL,
               weighted = FALSE)
-}
+}
diff --git a/R/prediction_bigglm.R b/R/prediction_bigglm.R
@@ -1,5 +1,5 @@
-# @rdname prediction
-# @export
+#' @rdname prediction
+#' @export
 prediction.bigglm <- 
 function(model, 
          data = find_data(model, parent.frame()), 

diff --git a/R/prediction_lda.R b/R/prediction_lda.R
@@ -1,5 +1,5 @@
-# @rdname prediction
-# @export
+#' @rdname prediction
+#' @export
 prediction.lda <- 
 function(model, 
          data = find_data(model, parent.frame()), 

diff --git a/R/prediction_mlogit.R b/R/prediction_mlogit.R
@@ -1,5 +1,5 @@
-# @rdname prediction
-# @export
+#' @rdname prediction
+#' @export
 prediction.mlogit <- 
 function(model, 
          data = find_data(model, parent.frame()), 

diff --git a/R/prediction_mnlogit.R b/R/prediction_mnlogit.R
@@ -1,5 +1,5 @@
-# @rdname prediction
-# @export
+#' @rdname prediction
+#' @export
 prediction.mnlogit <- 
 function(model, 
          data = find_data(model, parent.frame()), 
@@ -61,4 +61,4 @@ function(model,
               jacobian = NULL,
               category = category,
               weighted = FALSE)
-}
+}
diff --git a/R/prediction_naiveBayes.R b/R/prediction_naiveBayes.R
@@ -1,5 +1,5 @@
-# @rdname prediction
-# @export
+#' @rdname prediction
+#' @export
 prediction.naiveBayes <- 
 function(model, 
          data = find_data(model, parent.frame()), 

diff --git a/R/prediction_qda.R b/R/prediction_qda.R
@@ -1,5 +1,5 @@
-# @rdname prediction
-# @export
+#' @rdname prediction
+#' @export
 prediction.qda <- 
 function(model, 
          data = find_data(model, parent.frame()), 

diff --git a/R/prediction_tree.R b/R/prediction_tree.R
@@ -1,5 +1,5 @@
-# @rdname prediction
-# @export
+#' @rdname prediction
+#' @export
 prediction.tree <-
 function(model,
          data = find_data(model, parent.frame()),

diff --git a/R/prediction_vgam.R b/R/prediction_vgam.R
@@ -1,5 +1,5 @@
-# @rdname prediction
-# @export
+#' @rdname prediction
+#' @export
 prediction.vgam <- 
 function(model, 
          data = find_data(model, parent.frame()), 

diff --git a/R/prediction_vglm.R b/R/prediction_vglm.R
@@ -1,5 +1,5 @@
-# @rdname prediction
-# @export
+#' @rdname prediction
+#' @export
 prediction.vglm <- 
 function(model, 
          data = find_data(model, parent.frame()), 

diff --git a/README.md b/README.md
@@ -5,7 +5,7 @@ output: github_document
 
 <img src="man/figures/logo.png" align="right" />
 
-The **prediction** and **margins** packages are a combined effort to port the functionality of Stata's (closed source) [`margins`](http://www.stata.com/help.cgi?margins) command to (open source) R. **prediction** is focused on one function - `prediction()` - that provides type-safe methods for generating predictions from fitted regression models. `prediction()` is an S3 generic, which always return a `"data.frame"` class object rather than the mix of vectors, lists, etc. that are returned by the `predict()` methods for various model types. It provides a key piece of underlying infrastructure for the **margins** package. Users interested in generating marginal (partial) effects, like those generated by Stata's `margins, dydx(*)` command, should consider using `margins()` from the sibling project, [**margins**](https://cran.r-project.org/package=margins).
+The **prediction** and **margins** packages are a combined effort to port the functionality of Stata's (closed source) [`margins`](https://www.stata.com/help.cgi?margins) command to (open source) R. **prediction** is focused on one function - `prediction()` - that provides type-safe methods for generating predictions from fitted regression models. `prediction()` is an S3 generic, which always return a `"data.frame"` class object rather than the mix of vectors, lists, etc. that are returned by the `predict()` methods for various model types. It provides a key piece of underlying infrastructure for the **margins** package. Users interested in generating marginal (partial) effects, like those generated by Stata's `margins, dydx(*)` command, should consider using `margins()` from the sibling project, [**margins**](https://cran.r-project.org/package=margins).
 
 In addition to `prediction()`, this package provides a number of utility functions for generating useful predictions:
 
@@ -170,10 +170,9 @@ The currently supported model classes are:
 
 [![CRAN](https://www.r-pkg.org/badges/version/prediction)](https://cran.r-project.org/package=prediction)
 ![Downloads](https://cranlogs.r-pkg.org/badges/prediction)
-[![Build Status](https://travis-ci.org/leeper/prediction.svg?branch=master)](https://travis-ci.org/leeper/prediction)
 [![Build status](https://ci.appveyor.com/api/projects/status/a4tebeoa98cq07gy/branch/master?svg=true)](https://ci.appveyor.com/project/leeper/prediction/branch/master)
-[![codecov.io](https://codecov.io/github/leeper/prediction/coverage.svg?branch=master)](https://codecov.io/github/leeper/prediction?branch=master)
-[![Project Status: Active - The project has reached a stable, usable state and is being actively developed.](http://www.repostatus.org/badges/latest/active.svg)](http://www.repostatus.org/#active)
+[![codecov.io](https://app.codecov.io/github/leeper/prediction?branch=master)](https://app.codecov.io/github/leeper/prediction?branch=master)
+[![Project Status: Active - The project has reached a stable, usable state and is being actively developed.](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)
 
 The development version of this package can be installed directly from GitHub using `remotes`:
 

diff --git a/inst/CITATION b/inst/CITATION
diff --git a/man/find_data.Rd b/man/find_data.Rd
diff --git a/man/margex.Rd b/man/margex.Rd