Merge branch 'main' into strengejacke/issue954

R/find_parameters_other.R

@@ -9,6 +9,8 @@
 #' @inheritParams find_parameters.betamfx
 #' @inheritParams find_predictors
 #'
+#' @inheritSection find_predictors Model components
+#'
 #' @return A list of parameter names. The returned list may have following
 #' elements, usually requested via the `component` argument:
 #'
@@ -18,10 +20,11 @@
 #' - `survival` for model of class `mjoint`.
 #' - `extra` for models of class `glmx`.
 #'
-#' @examples
-#' data(mtcars)
-#' m <- lm(mpg ~ wt + cyl + vs, data = mtcars)
+#' @examplesIf requireNamespace("betareg", quietly = TRUE)
+#' data("GasolineYield", package = "betareg")
+#' m <- betareg::betareg(yield ~ batch + temp, data = GasolineYield)
 #' find_parameters(m)
+#' find_parameters(m, component = "precision")
 #' @export
 find_parameters.averaging <- function(x, component = "conditional", flatten = FALSE, ...) {
   component <- validate_argument(component, c("conditional", "full"))

R/find_predictors.R

@@ -56,6 +56,9 @@
 #' - **averaging**:`"conditional"` and `"full"`
 #' - **mjoint**: `"survival"`
 #' - **mfx**: `"precision"`, `"marginal"`
+#' - **betareg**, **DirichletRegModel**: `"precision"`
+#' - **mvord**: `"thresholds"` and `"correlation"`
+#' - **clm2**: `"scale"`
 #'
 #' For models of class `brmsfit` (package **brms**), `component`, even more
 #' options are possible for the `component` argument, which are not all

R/get_parameters_others.R

@@ -13,15 +13,17 @@
 #' @return A data frame with three columns: the parameter names, the related
 #'   point estimates and the component.
 #'
-#' @examples
-#' data(mtcars)
-#' m <- lm(mpg ~ wt + cyl + vs, data = mtcars)
+#' @examplesIf requireNamespace("betareg", quietly = TRUE)
+#' data("GasolineYield", package = "betareg")
+#' m <- betareg::betareg(yield ~ batch + temp, data = GasolineYield)
 #' get_parameters(m)
+#' get_parameters(m, component = "precision")
 #' @export
-get_parameters.betareg <- function(x,
-                                   component = c("all", "conditional", "precision", "location", "distributional", "auxiliary"),
-                                   ...) {
-  component <- match.arg(component)
+get_parameters.betareg <- function(x, component = "all", ...) {
+  component <- validate_argument(
+    component,
+    c("all", "conditional", "precision", "location", "distributional", "auxiliary")
+  )
   cf <- stats::coef(x)
 
   params <- data.frame(
@@ -40,10 +42,9 @@ get_parameters.betareg <- function(x,
 }
 
 
-#' @rdname get_parameters.betareg
 #' @export
-get_parameters.glmgee <- function(x, component = c("all", "conditional", "dispersion"), ...) {
-  component <- match.arg(component)
+get_parameters.glmgee <- function(x, component = "all", ...) {
+  component <- validate_argument(component, c("all", "conditional", "dispersion"))
 
   junk <- utils::capture.output({
     cs <- suppressWarnings(stats::coef(summary(x, corr = FALSE)))
@@ -99,12 +100,12 @@ get_parameters.nestedLogit <- function(x, component = "all", verbose = TRUE, ...
 }
 
 
-#' @rdname get_parameters.betareg
 #' @export
-get_parameters.DirichletRegModel <- function(x,
-                                             component = c("all", "conditional", "precision", "location", "distributional", "auxiliary"),
-                                             ...) {
-  component <- match.arg(component)
+get_parameters.DirichletRegModel <- function(x, component = "all", ...) {
+  component <- validate_argument(
+    component,
+    c("all", "conditional", "precision", "location", "distributional", "auxiliary")
+  )
   cf <- stats::coef(x)
 
   if (x$parametrization == "common") {
@@ -139,12 +140,9 @@ get_parameters.DirichletRegModel <- function(x,
 }
 
 
-#' @rdname get_parameters.betareg
 #' @export
-get_parameters.averaging <- function(x,
-                                     component = c("conditional", "full"),
-                                     ...) {
-  component <- match.arg(component)
+get_parameters.averaging <- function(x, component = "conditional", ...) {
+  component <- validate_argument(component, c("conditional", "full"))
   cf <- stats::coef(x, full = component == "full")
 
   params <- data.frame(
@@ -158,12 +156,12 @@ get_parameters.averaging <- function(x,
 }
 
 
-#' @rdname get_parameters.betareg
 #' @export
-get_parameters.glmx <- function(x,
-                                component = c("all", "conditional", "extra", "location", "distributional", "auxiliary"),
-                                ...) {
-  component <- match.arg(component)
+get_parameters.glmx <- function(x, component = "all", ...) {
+  component <- validate_argument(
+    component,
+    c("all", "conditional", "extra", "location", "distributional", "auxiliary")
+  )
   cf <- stats::coef(summary(x))
 
   params <- rbind(
@@ -191,12 +189,9 @@ get_parameters.glmx <- function(x,
 }
 
 
-#' @rdname get_parameters.betareg
 #' @export
-get_parameters.clm2 <- function(x,
-                                component = c("all", "conditional", "scale"),
-                                ...) {
-  component <- match.arg(component)
+get_parameters.clm2 <- function(x, component = "all", ...) {
+  component <- validate_argument(component,c("all", "conditional", "scale"))
 
   cf <- stats::coef(summary(x))
   n_intercepts <- length(x$xi)
@@ -223,12 +218,12 @@ get_parameters.clm2 <- function(x,
 get_parameters.clmm2 <- get_parameters.clm2
 
 
-#' @rdname get_parameters.betareg
 #' @export
-get_parameters.mvord <- function(x,
-                                 component = c("all", "conditional", "thresholds", "correlation"),
-                                 ...) {
-  component <- match.arg(component)
+get_parameters.mvord <- function(x, component = "all", ...) {
+  component <- validate_argument(
+    component,
+    c("all", "conditional", "thresholds", "correlation")
+  )
   junk <- utils::capture.output(s <- summary(x)) # nolint
   # intercepts thresholds
   thresholds <- as.data.frame(s$thresholds)
@@ -278,13 +273,9 @@ get_parameters.mvord <- function(x,
 }
 
 
-
-#' @rdname get_parameters.betareg
 #' @export
-get_parameters.mjoint <- function(x,
-                                  component = c("all", "conditional", "survival"),
-                                  ...) {
-  component <- match.arg(component)
+get_parameters.mjoint <- function(x, component = "all", ...) {
+  component <- validate_argument(component, c("all", "conditional", "survival"))
   s <- summary(x)
 
   params <- rbind(
@@ -312,7 +303,6 @@ get_parameters.mjoint <- function(x,
 }
 
 
-
 #' @export
 get_parameters.systemfit <- function(x, ...) {
   cf <- stats::coef(summary(x))
@@ -335,6 +325,7 @@ get_parameters.systemfit <- function(x, ...) {
   do.call(rbind, out)
 }
 
+
 #' @export
 get_parameters.marginaleffects <- function(x, summary = FALSE, merge_parameters = FALSE, ...) {
   # check if we have a Bayesian model here