document methods

.Rbuildignore

@@ -10,3 +10,4 @@
 ^README\.Rmd$
 ^README\.html$
 ^pkgdown$
+^Makefile$

NAMESPACE

@@ -35,6 +35,7 @@ importFrom(Formula,Formula)
 importFrom(MASS,negative.binomial)
 importFrom(MASS,theta.ml)
 importFrom(dplyr,across)
+importFrom(dplyr,all_of)
 importFrom(dplyr,filter)
 importFrom(dplyr,group_by)
 importFrom(dplyr,mutate)

R/capybara-package.R

@@ -12,7 +12,7 @@
 #' and Wanner (2020).
 #'
 #' @name capybara-package
-#' @importFrom dplyr across filter group_by mutate mutate_at select
+#' @importFrom dplyr across all_of filter group_by mutate mutate_at select
 #'  summarise ungroup vars where
 #' @importFrom rlang sym :=
 #' @importFrom Formula Formula

R/generics_summary.R

@@ -1,6 +1,7 @@
+#' @title Summary method for fixed effects APEs
+#' @inherit vcov.apes
 #' @export
-#' @noRd
-summary.apes <- function(object) {
+summary.apes <- function(object, ...) {
   # Compute coefficent matrix
   est <- object[["delta"]]
   se <- sqrt(diag(object[["vcov"]]))
@@ -14,11 +15,13 @@ summary.apes <- function(object) {
   structure(list(cm = cm), class = "summary.apes")
 }
 
+#' @title Summary method for fixed effects GLMs
+#' @inherit vcov.feglm
 #' @export
-#' @noRd
 summary.feglm <- function(
     object,
-    type = c("hessian", "outer.product", "sandwich", "clustered")) {
+    type = c("hessian", "outer.product", "sandwich", "clustered"),
+    ...) {
   # Compute coefficients matrix
   est <- object[["coefficients"]]
   se <- sqrt(diag(vcov(object, type)))
@@ -58,11 +61,13 @@ summary.feglm <- function(
   structure(res, class = "summary.feglm")
 }
 
+#' @title Summary method for fixed effects LMs
+#' @inherit vcov.felm
 #' @export
-#' @noRd
 summary.felm <- function(
     object,
-    type = "hessian") {
+    type = "hessian",
+    ...) {
   # Compute coefficients matrix
   est <- object[["coefficients"]]
   se <- sqrt(diag(vcov(object, type)))

R/generics_vcov.R

@@ -2,10 +2,11 @@
 #' @description Covariance matrix for the estimator of the
 #'  average partial effects from objects returned by \code{\link{apes}}.
 #' @param object an object of class \code{"apes"}.
+#' @param ... additional arguments.
 #' @return A named matrix of covariance estimates.
 #' @seealso \code{\link{apes}}
 #' @export
-vcov.apes <- function(object) {
+vcov.apes <- function(object, ...) {
   object[["vcov"]]
 }
 
@@ -20,14 +21,16 @@ vcov.apes <- function(object) {
 #'  estimator. \code{"sandwich"} is the sandwich estimator (sometimes also
 #'  referred as robust estimator), and \code{"clustered"} computes a clustered
 #'  covariance matrix given some cluster variables.
+#' @param ... additional arguments.
 #' @return A named matrix of covariance estimates.
 #' @references Cameron, C., J. Gelbach, and D. Miller (2011). "Robust Inference
 #'  With Multiway Clustering". Journal of Business & Economic Statistics 29(2).
 #' @seealso \code{\link{feglm}}
 #' @export
 vcov.feglm <- function(
     object,
-    type = c("hessian", "outer.product", "sandwich", "clustered")) {
+    type = c("hessian", "outer.product", "sandwich", "clustered"),
+    ...) {
   # Check validity of input argument 'type'
   type <- match.arg(type)
 
@@ -159,6 +162,7 @@ vcov.feglm <- function(
 #' @export
 vcov.felm <- function(
     object,
-    type = c("hessian", "outer.product", "sandwich", "clustered")) {
+    type = c("hessian", "outer.product", "sandwich", "clustered"),
+    ...) {
   vcov.feglm(object, type)
 }

docs/pkgdown.yml

@@ -3,5 +3,5 @@ pkgdown: 2.0.7
 pkgdown_sha: ~
 articles:
   intro: intro.html
-last_built: 2024-02-08T00:11Z
+last_built: 2024-02-14T19:48Z