fix namespace

DESCRIPTION

@@ -3,15 +3,16 @@ Type: Package
 Title: lightning-fast staggered Difference-in-Difference estimators
 Version: 0.9
 Date: 2023-10-06
-Author@R: c(person(given = "Lin-Tung",
-           family = "Tsai",
-           role = "aut",
-    person(given = "Maxwell",
-           family = "Kellogg",
-           role = "aut"),
-    person(given = "Kuan-Ju",
-           family = "Tseng",
-           role = "aut"))
+Authors@R: c(
+  person("Lin-Tung","Tsai",
+         role = c("aut", "cre"),
+         email = "[email protected]"),
+  person(given = "Maxwell",
+         family = "Kellogg", ,
+         role = "aut"),
+  person(given = "Kuan-Ju",
+         family = "Tseng", ,
+          role = "aut"))
 Maintainer: Lin-Tung Tsai <[email protected]>
 Description: **fastdid** is a lightning-fast implementation of Callaway and Sant'Anna's (2021)<https://www.sciencedirect.com/science/article/pii/S0304407620303948> staggered Difference-in-Differences (DiD) estimators that speeds up the process by magnitudes. With fastdid You can run DiD designs for millions of units in just seconds, not hours. 
 License: GPL (>= 2)
@@ -21,8 +22,7 @@ Imports:
     BMisc,
     collapse,
     dreamerr,
-    speedglm,
-    stringr
+    speedglm
 Suggests: ggplot2, did
 Encoding: UTF-8
 RoxygenNote: 7.2.3

NAMESPACE

@@ -1,11 +1,18 @@
 # Generated by roxygen2: do not edit by hand
 
 export(fastdid)
+export(plot_did_dynamics)
 export(sim_did)
 import(BMisc)
 import(collapse)
 import(data.table)
 import(dreamerr)
-import(ggplot2)
 import(speedglm)
 import(stringr)
+importFrom(stats,binomial)
+importFrom(stats,fitted)
+importFrom(stats,qnorm)
+importFrom(stats,quantile)
+importFrom(stats,rnorm)
+importFrom(stats,sd)
+importFrom(stats,vcov)

R/aggregate_gt.R

@@ -29,8 +29,6 @@ aggregate_gt <- function(gt_result, cohort_sizes,
     #aggregated att
     agg_att <- weights %*% gt_att
 
-
-
     #get the influence from weight estimation
     #this needs to be optimized!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
     inf_weights <- sapply(asplit(weights, 1), function (x){

R/estimate_did.R

@@ -18,7 +18,7 @@ estimate_did <- function(dt_did, last_coef = NULL){
   #the intercept is essential
   if(ipw){
     prop_score_est <- suppressWarnings(speedglm(dt_did[,D] ~ as.matrix(dt_did[,.SD, .SDcols = covvars]), 
-                                                family = binomial(), fitted = TRUE, start = last_coef,
+                                                family = stats::binomial(), fitted = TRUE, start = last_coef,
                                                 weights = dt_did[, weights]))
     logit_coef <-  prop_score_est$coefficients 
     logit_coef[is.na(logit_coef)|abs(logit_coef) > 1e10] <- 0 #put extreme value and na to 0
@@ -55,7 +55,7 @@ estimate_did <- function(dt_did, last_coef = NULL){
   # influence from ipw
   if(ipw){
     score_ps <- as.matrix(dt_did[, weights*(D-ps)*.SD, .SDcols = covvars]) |> reverse_col()
-    hess <- vcov(prop_score_est) * n
+    hess <- stats::vcov(prop_score_est) * n
     asym_linear_ps <- score_ps %*% hess
     M2 <- dt_did[, .(cont_ipw_weight*(delta_y-weighted_cont_delta)*.SD), .SDcols = covvars][, lapply(.SD, mean), .SDcols = covvars] |> 
       as.matrix()|> reverse_col()

R/fastdid.R

@@ -17,8 +17,8 @@
 #' @param copy whether to copy the dataset before processing, set to true if the original dataset is to be re-used.
 #' @param validate whether to validate the dataset before processing.
 #' 
-#' @import data.table speedglm stringr collapse dreamerr BMisc
-#' 
+#' @import data.table speedglm stringr collapse dreamerr BMisc 
+#' @importFrom stats quantile vcov sd binomial fitted qnorm rnorm
 #' @return A data.table containing the estimated treatment effects and standard errors.
 #' @export
 #'
@@ -28,15 +28,21 @@
 #' dt <- simdt$dt
 #' 
 #' #basic call
-#' result <- fastdid(dt, timevar = "time", cohortvar = "G", unitvar = "unit", outcomevar = "y",  result_type = "group_time")
+#' result <- fastdid(dt, timevar = "time", cohortvar = "G", 
+#'                   unitvar = "unit", outcomevar = "y",  
+#'                   result_type = "group_time")
 #' 
 #' #control for covariates
-#' result2 <- fastdid(dt, timevar = "time", cohortvar = "G", unitvar = "unit", outcomevar = "y",  result_type = "group_time",
-#'                   covariatesvar = c("x", "x2"))
+#' result2 <- fastdid(dt, timevar = "time", cohortvar = "G", 
+#'                    unitvar = "unit", outcomevar = "y",  
+#'                    result_type = "group_time",
+#'                    covariatesvar = c("x", "x2"))
 #'                   
 #' #bootstrap and clustering
-#' result3 <- fastdid(dt, timevar = "time", cohortvar = "G", unitvar = "unit", outcomevar = "y",  result_type = "group_time",
-#'                   boot = TRUE, clustervar = "x")
+#' result3 <- fastdid(dt, timevar = "time", cohortvar = "G", 
+#'                    unitvar = "unit", outcomevar = "y",  
+#'                    result_type = "group_time",
+#'                    boot = TRUE, clustervar = "x")
 #'
 #' @keywords difference-in-differences fast computation panel data estimation did
 fastdid <- function(dt,

R/get_se.R

@@ -5,14 +5,14 @@ get_se <- function(inf_matrix, boot, biters, cluster) {
     top_quant <- 0.75
     bot_quant <- 0.25
     if(!is.null(cluster)){
-      cluster_n <- aggregate(cluster, by=list(cluster), length)[,2]
+      cluster_n <- stats::aggregate(cluster, by=list(cluster), length)[,2]
       inf_matrix <- fsum(inf_matrix, cluster) / cluster_n #the mean without 0 for each cluster of each setting
     }
 
     boot_results <- BMisc::multiplier_bootstrap(inf_matrix, biters = biters) %>% as.data.table()
 
-    boot_top <- boot_results[, lapply(.SD, function(x) quantile(x, top_quant, type=1, na.rm = TRUE)),]
-    boot_bot <- boot_results[, lapply(.SD, function(x) quantile(x, bot_quant, type=1, na.rm = TRUE)),]
+    boot_top <- boot_results[, lapply(.SD, function(x) stats::quantile(x, top_quant, type=1, na.rm = TRUE)),]
+    boot_bot <- boot_results[, lapply(.SD, function(x) stats::quantile(x, bot_quant, type=1, na.rm = TRUE)),]
 
     dt_se <- rbind(boot_bot, boot_top) %>% transpose()
     names(dt_se) <- c("boot_bot", "boot_top")

R/global.R

@@ -0,0 +1,19 @@
+NULL
+
+if(FALSE){
+  text <- ". agg_weight att att_cont att_treat attgt cohort cohort_size
+    conf_lwb conf_upb const cont_ipw_weight count delta_y element_rect
+    element_text event_time pg placeholder post.y pre.y ps s se target
+    tau time_fe treat_ipw_weight treat_latent type unit unit_fe weight x
+    x2 x_trend y y0 y1 y2 time"
+  text <- text |> str_remove_all("\\\n") |>str_split(" ") |> unlist()
+  text <- text[text!=""]
+  text <- text |> str_flatten(collapse = "','")
+  text <- paste0("c('", text, "')")
+}
+
+# quiets concerns of R CMD check re: the .'s that appear in pipelines and data.table variables
+utils::globalVariables(c('.','agg_weight','att','att_cont','att_treat','attgt','cohort','cohort_size','conf_lwb','conf_upb',
+                         'const','cont_ipw_weight','count','delta_y','element_rect','element_text','event_time','pg','placeholder',
+                         'post.y','pre.y','ps','s','se','target','tau','time_fe',
+                         'treat_ipw_weight','treat_latent','type','unit','unit_fe','weight','x','x2','x_trend','y','y0','y1','y2', 'time', 'weights'))

R/plot_event_dynamics.R

@@ -9,14 +9,19 @@
 #' @param significance_level The significance level for confidence intervals (default is 0.05).
 #'
 #' @return A ggplot2 object representing the event study plot.
-#'
-#' @import ggplot2
+#' @export
 
 plot_did_dynamics <-function(dt, 
-                             graphname = "event study plot", note = "", base_time = -1, significance_level = 0.05, 
-                             stratify_offset =0.1
+                             graphname = "event study plot", note = "", base_time = -1, significance_level = 0.05#, 
+                             #stratify_offset =0.1
 ){
-
+
+  if (!requireNamespace("ggplot2", quietly = TRUE)) {
+    warning("The ggplot2 package must be installed to use plotting functions")
+    #Either exit or do something without rgl
+    return(NULL)
+  }
+
 
   #add the base period
   base_row <- data.table(att = 0, se = 0, event_time = base_time)
@@ -32,18 +37,18 @@ plot_did_dynamics <-function(dt,
   # }
 
   figure <- dt |> 
-    ggplot() +
-    geom_hline(yintercept = 0, linetype = 'dashed', col = 'red')
+    ggplot2::ggplot() +
+    ggplot2::geom_hline(yintercept = 0, linetype = 'dashed', col = 'red')
 
   # if("stratify" %in% names(dt)){
   #   figure <- figure + geom_line(aes(x = event_time, y = att, color = stratify)) + 
   #     geom_point(aes(x = event_time, y = att, color = stratify)) +
   #     geom_errorbar(aes(x = event_time, ymin = conf_lwb, ymax = conf_upb), 
   #                   width = 0.1, linetype = "dashed")
   # } else {
-    figure <- figure + geom_line(aes(x = event_time, y = att), color = "black") + 
-    geom_point(aes(x = event_time, y = att), color = "black") +
-    geom_errorbar(aes(x = event_time, ymin = conf_lwb, ymax = conf_upb), 
+    figure <- figure + ggplot2::geom_line(ggplot2::aes(x = event_time, y = att), color = "black") + 
+      ggplot2::geom_point(ggplot2::aes(x = event_time, y = att), color = "black") +
+      ggplot2::geom_errorbar(ggplot2::aes(x = event_time, ymin = conf_lwb, ymax = conf_upb), 
                   width = 0.1, linetype = "dashed")
   # }
 
@@ -55,14 +60,14 @@ plot_did_dynamics <-function(dt,
   # }
 
   figure <- figure +
-    theme_classic() +
-    theme(legend.position = "bottom",
+    ggplot2::theme_classic() +
+    ggplot2::theme(legend.position = "bottom",
           legend.background = element_rect(linetype = "dashed", color = "black"),
           legend.box = "horizontal",
           plot.title = element_text(hjust = 0.5),
           plot.subtitle = element_text(hjust = 0.5),
           plot.caption = element_text(hjust = 0)) +
-    labs(title = graphname, subtitle = note)
+    ggplot2::labs(title = graphname, subtitle = note)
 
   return(figure)
 

R/utils.R

@@ -2,9 +2,8 @@
 
 
 set_max_thread <- function(){
-  setDTthreads(0)
+  data.table::setDTthreads(0)
   options(kit.nThread = getDTthreads())
-  setFixest_nthreads(getDTthreads())
 }
 
 reverse_col <- function(x){

R/validate_did.R

@@ -20,7 +20,7 @@ validate_did <- function(dt, covariatesvar){
     }
 
     #check covaraites is not constant  
-    if(any(sapply(dt[1:raw_unit_size, .SD, .SDcols = covariatesvar], sd) == 0)){stop("some covariates have no variation")}
+    if(any(sapply(dt[1:raw_unit_size, .SD, .SDcols = covariatesvar], stats::sd) == 0)){stop("some covariates have no variation")}
   }
 
   #check balanced panel

interactive/test_all.R → interactive/pkg_dev.R

@@ -14,6 +14,11 @@ if(FALSE){
   test_all()
 }
 
+if(FALSE){
+  roxygenise()
+  build()
+  check()
+}
 
 if(FALSE){
   use_github_actions()