partial changes for ropensci standard

DESCRIPTION

@@ -37,10 +37,10 @@ LazyData: true
 RoxygenNote: 7.3.1
 Encoding: UTF-8
 NeedsCompilation: yes
-LinkingTo: cpp11, cpp11armadillo
+LinkingTo: cpp11, armadillo
 VignetteBuilder: knitr
 Config/testthat/edition: 3
 Remotes: 
-    pachadotdev/cpp11armadillo,
+    pachadotdev/armadillo,
     ropenscilabs/srr
 Roxygen: list(markdown = TRUE, roclets = c("namespace", "rd", "srr::srr_stats_roclet"))

NAMESPACE

@@ -32,6 +32,7 @@ export(apes)
 export(augment)
 export(bias_corr)
 export(feglm)
+export(feglm_control)
 export(felm)
 export(fenegbin)
 export(fepoisson)

R/feglm.R

@@ -100,10 +100,10 @@ feglm <- function(
   k <- length(k_vars)
 
   # Generate temporary variable ----
-  tmp.var <- temp_var_(data)
+  tmp_var <- temp_var_(data)
 
   # Drop observations that do not contribute to the log likelihood ----
-  data <- drop_by_link_type_(data, lhs, family, tmp.var, k_vars, control)
+  data <- drop_by_link_type_(data, lhs, family, tmp_var, k_vars, control)
 
   # Transform fixed effects and clusters to factors ----
   data <- transform_fe_(data, formula, k_vars)

R/feglm_control.R

@@ -32,6 +32,8 @@
 #' @return A named list of control parameters.
 #'
 #' @seealso \code{\link{feglm}}
+#' 
+#' @export
 feglm_control <- function(
     dev_tol = 1.0e-08,
     center_tol = 1.0e-08,

R/feglm_offset.R

@@ -1,5 +1,13 @@
-# Efficient offset algorithm to update the linear predictor ----
-
+#' @title GLM offset
+#' 
+#' @description Efficient offset algorithm to update the linear predictor
+#' 
+#' @param object an object of class \code{feglm}
+#' @param offset a numeric vector of length equal to the number of observations
+#' 
+#' @return an object of class \code{feglm}
+#' 
+#' @noRd
 feglm_offset_ <- function(object, offset) {
   # Check validity of 'object'
   if (!inherits(object, "feglm")) {

R/fixed_effects.R

@@ -1,19 +1,25 @@
 #' @title Recover the estimates of the fixed effects after fitting (G)LMs
+#' 
 #' @description The system might not have a unique solution since we do not take
 #'  collinearity into account. If the solution is not unique, an estimable
 #'  function has to be applied to our solution to get meaningful estimates of
 #'  the fixed effects.
+#' 
 #' @param object an object of class \code{"feglm"}.
 #' @param alpha_tol tolerance level for the stopping condition. The algorithm is
 #'  stopped at iteration \eqn{i} if \eqn{||\boldsymbol{\alpha}_{i} -
 #'  \boldsymbol{\alpha}_{i - 1}||_{2} < tol ||\boldsymbol{\alpha}_{i - 1}||
 #'  {2}}{||\Delta \alpha|| < tol ||\alpha_old||}. Default is \code{1.0e-08}.
+#' 
 #' @return A named list containing named vectors of estimated fixed effects.
+#' 
 #' @references Stammann, A. (2018). "Fast and Feasible Estimation of Generalized
 #'  Linear Models with High-Dimensional k-way Fixed Effects". ArXiv e-prints.
 #' @references Gaure, S. (n. d.). "Multicollinearity, identification, and
 #'  estimable functions". Unpublished.
+#' 
 #' @seealso \code{\link{felm}}, \code{\link{feglm}}
+#' 
 #' @examples
 #' # same as the example in feglm but extracting the fixed effects
 #' mod <- fepoisson(
@@ -22,6 +28,7 @@
 #' )
 #'
 #' fixed_effects(mod)
+#' 
 #' @export
 fixed_effects <- function(object = NULL, alpha_tol = 1.0e-08) {
   # Check validity of 'object'

R/generics_glance.R

@@ -2,6 +2,8 @@
 #' @export
 generics::glance
 
+#' @title Glance method for 'feglm' objects
+#' @description Integration with the 'broom' package
 #' @export
 #' @noRd
 glance.feglm <- function(x, ...) {
@@ -21,6 +23,8 @@ glance.feglm <- function(x, ...) {
   res
 }
 
+#' @title Glance method for 'felm' objects
+#' @description Integration with the 'broom' package
 #' @export
 #' @noRd
 glance.felm <- function(x, ...) {

R/generics_predict.R

@@ -1,3 +1,5 @@
+#' @title Predict method for 'feglm' objects
+#' @description Similar to the 'predict' method for 'glm' objects
 #' @export
 #' @noRd
 predict.feglm <- function(object, type = c("link", "response"), ...) {
@@ -14,6 +16,8 @@ predict.feglm <- function(object, type = c("link", "response"), ...) {
   x
 }
 
+#' @title Predict method for 'felm' objects
+#' @description Similar to the 'predict' method for 'lm' objects
 #' @export
 #' @noRd
 predict.felm <- function(object, ...) {

R/generics_print.R

@@ -1,8 +1,14 @@
+#' @title Refactors for and 'feglm' summaries
+#' @description Reduces the cyclomatic complexity of print.summary.feglm
+#' @noRd
 summary_formula_ <- function(x) {
   cat("Formula: ")
   print(x[["formula"]])
 }
 
+#' @title Refactors for and 'feglm' summaries
+#' @description Reduces the cyclomatic complexity of print.summary.feglm
+#' @noRd
 summary_family_ <- function(x) {
   cat(
     "\nFamily: ", gsub("^([a-z])", "\\U\\1", x[["family"]][["family"]],
@@ -12,6 +18,9 @@ summary_family_ <- function(x) {
   )
 }
 
+#' @title Refactors for and 'feglm' summaries
+#' @description Reduces the cyclomatic complexity of print.summary.feglm
+#' @noRd
 summary_estimates_ <- function(x, digits) {
   cat("\nEstimates:\n\n")
   coefmat <- as.data.frame(x[["cm"]])
@@ -113,6 +122,9 @@ summary_estimates_ <- function(x, digits) {
   cat("\nSignificance codes: *** 99.9%; ** 99%; * 95%; . 90%\n")
 }
 
+#' @title Refactors for and 'feglm' summaries
+#' @description Reduces the cyclomatic complexity of print.summary.feglm
+#' @noRd
 summary_r2_ <- function(x, digits) {
   cat(
     sprintf("\nR-squared%*s:", nchar("Adj. "), " "),
@@ -124,6 +136,9 @@ summary_r2_ <- function(x, digits) {
   )
 }
 
+#' @title Refactors for and 'feglm' summaries
+#' @description Reduces the cyclomatic complexity of print.summary.feglm
+#' @noRd
 summary_pseudo_rsq_ <- function(x, digits) {
   if (x[["family"]][["family"]] == "poisson") {
     cat(
@@ -133,6 +148,9 @@ summary_pseudo_rsq_ <- function(x, digits) {
   }
 }
 
+#' @title Refactors for and 'feglm' summaries
+#' @description Reduces the cyclomatic complexity of print.summary.feglm
+#' @noRd
 summary_nobs_ <- function(x) {
   cat(
     "\nNumber of observations:",
@@ -142,6 +160,9 @@ summary_nobs_ <- function(x) {
   )
 }
 
+#' @title Refactors for and 'feglm' summaries
+#' @description Reduces the cyclomatic complexity of print.summary.feglm
+#' @noRd
 summary_fisher_ <- function(x, digits) {
   if (is.null(x[["theta"]])) {
     cat("\nNumber of Fisher Scoring iterations:", x[["iter"]], "\n")
@@ -159,12 +180,16 @@ summary_fisher_ <- function(x, digits) {
   }
 }
 
+#' @title Print method for 'apes' objects
+#' @description Similar to the 'print' method for 'glm' objects
 #' @export
 #' @noRd
 print.apes <- function(x, digits = max(3L, getOption("digits") - 3L), ...) {
   print(x[["delta"]], digits = digits)
 }
 
+#' @title Print method for 'feglm' objects
+#' @description Similar to the 'print' method for 'glm' objects
 #' @export
 #' @noRd
 print.feglm <- function(x, digits = max(3L, getOption("digits") - 3L), ...) {
@@ -177,12 +202,16 @@ print.feglm <- function(x, digits = max(3L, getOption("digits") - 3L), ...) {
   print(x[["coefficients"]], digits = digits)
 }
 
+#' @title Print method for 'felm' objects
+#' @description Similar to the 'print' method for 'lm' objects
 #' @export
 #' @noRd
 print.felm <- function(x, digits = max(3L, getOption("digits") - 3L), ...) {
   print(x[["coefficients"]], digits = digits)
 }
 
+#' @title Print method for 'apes' summary objects
+#' @description Similar to the 'print' method for 'glm' objects
 #' @export
 #' @noRd
 print.summary.apes <- function(
@@ -191,6 +220,8 @@ print.summary.apes <- function(
   printCoefmat(x[["cm"]], P.values = TRUE, has.Pvalue = TRUE, digits = digits)
 }
 
+#' @title Print method for 'feglm' summary objects
+#' @description Similar to the 'print' method for 'glm' objects
 #' @export
 #' @noRd
 print.summary.feglm <- function(
@@ -209,6 +240,8 @@ print.summary.feglm <- function(
   summary_fisher_(x, digits)
 }
 
+#' @title Print method for 'felm' summary objects
+#' @description Similar to the 'print' method for 'lm' objects
 #' @export
 #' @noRd
 print.summary.felm <- function(

R/generics_tidy.R

@@ -2,6 +2,8 @@
 #' @export
 generics::tidy
 
+#' @title Tidy method for 'feglm' objects
+#' @description Integration with the 'broom' package
 #' @export
 #' @noRd
 tidy.feglm <- function(x, conf.int = FALSE, conf.level = 0.95, ...) {
@@ -15,6 +17,8 @@ tidy.feglm <- function(x, conf.int = FALSE, conf.level = 0.95, ...) {
   res
 }
 
+#' @title Tidy method for 'felm' objects
+#' @description Integration with the 'broom' package
 #' @export
 #' @noRd
 tidy.felm <- function(x, conf.int = FALSE, conf.level = 0.95, ...) {

R/generics_vcov.R

@@ -1,32 +1,45 @@
 #' @title Covariance matrix for APEs
+#' 
 #' @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
+#' 
 #' @noRd
 vcov.apes <- function(object, ...) {
   object[["vcov"]]
 }
 
 #' @title Covariance matrix for GLMs
+#' 
 #' @description Covariance matrix for the estimator of the structural parameters
 #'  from objects returned by \code{\link{feglm}}. The covariance is computed
 #' from the hessian, the scores, or a combination of both after convergence.
+#' 
 #' @param object an object of class \code{"feglm"}.
 #' @param type the type of covariance estimate required. \code{"hessian"} refers
 #'  to the inverse of the negative expected hessian after convergence and is the
 #'  default option. \code{"outer.product"} is the outer-product-of-the-gradient
 #'  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}}
+#' 
 #' @examples 
 #' mod <- fepoisson(
 #'  trade ~ log_dist + lang + cntg + clny | exp_year + imp_year | pair,
@@ -161,12 +174,17 @@ vcov.feglm <- function(
 }
 
 #' @title Covariance matrix for LMs
+#' 
 #' @description Covariance matrix for the estimator of the structural parameters
 #'  from objects returned by \code{\link{felm}}. The covariance is computed
-#' from the hessian, the scores, or a combination of both after convergence.
+#'  from the hessian, the scores, or a combination of both after convergence.
+#' 
 #' @param object an object of class \code{"felm"}.
+#' 
 #' @inherit vcov.feglm
+#'
 #' @seealso \code{\link{felm}}
+#' 
 #' @export
 vcov.felm <- function(
     object,