fix #39

NAMESPACE

@@ -44,7 +44,7 @@ export(cpsd_spade)
 export(ecological_detector)
 export(factor_detector)
 export(gd)
-export(gd_bestunidisc)
+export(gd_optunidisc)
 export(gen_permutations)
 export(geodetector)
 export(gozh)

R/gd_bestunidisc.R → R/gd_optunidisc.R

@@ -1,11 +1,9 @@
-#' @title best univariate discretization based on geodetector q-statistic
+#' @title optimal univariate discretization based on geodetector q-statistic
 #' @author Wenbo Lv \email{[email protected]}
-#' @description
-#' Function for determining the best univariate discretization based on geodetector q-statistic.
 #'
-#' @param formula A formula of best univariate discretization.
+#' @param formula A formula.
 #' @param data A `data.frame`, `tibble` or `sf` object of observation data.
-#' @param discnum (optional) A vector of number of classes for discretization. Default is `3:8`.
+#' @param discnum (optional) A vector of numbers of discretization. Default is `3:8`.
 #' @param discmethod (optional) A vector of methods for discretization, default is using
 #' `c("sd","equal","geometric","quantile","natural")` by invoking `sdsfun`.
 #' @param cores (optional) Positive integer (default is 1). When cores are greater than 1, use
@@ -25,13 +23,13 @@
 #'
 #' @examples
 #' data('sim')
-#' gd_bestunidisc(y ~ xa + xb + xc,
-#'                data = sim,
-#'                discnum = 3:6)
+#' gd_optunidisc(y ~ xa + xb + xc,
+#'               data = sim,
+#'               discnum = 3:6)
 #'
-gd_bestunidisc = \(formula, data, discnum = 3:8,
-                   discmethod = c("sd","equal","geometric","quantile","natural"),
-                   cores = 1, seed = 123456789, ...){
+gd_optunidisc = \(formula, data, discnum = 3:8,
+                  discmethod = c("sd","equal","geometric","quantile","natural"),
+                  cores = 1, seed = 123456789, ...){
   doclust = FALSE
   if (cores > 1) {
     doclust = TRUE

R/opgd.R

@@ -1,7 +1,5 @@
 #' @title optimal parameters-based geographical detector(OPGD) model
 #' @author Wenbo Lv \email{[email protected]}
-#' @description
-#' Function for optimal parameters-based geographical detector(OPGD) model.
 #' @references
 #' Song, Y., Wang, J., Ge, Y. & Xu, C. (2020) An optimal parameters-based geographical detector
 #' model enhances geographic characteristics of explanatory variables for spatial heterogeneity
@@ -55,9 +53,9 @@ opgd = \(formula, data, discvar = NULL, discnum = 3:8,
     discvar = colnames(data)[-which(colnames(data) == yname)]
   }
   discdf = dplyr::select(data,dplyr::all_of(c(yname,discvar)))
-  g = gd_bestunidisc(paste0(yname,'~',paste0(discvar,collapse = '+')),
-                     data = discdf, discnum = discnum,
-                     discmethod = discmethod, cores = cores, ...)
+  g = gd_optunidisc(paste0(yname,'~',paste0(discvar,collapse = '+')),
+                    data = discdf, discnum = discnum,
+                    discmethod = discmethod, cores = cores, ...)
   opt_param = tibble::as_tibble(g[1:3])
   names(opt_param) = c("varibale","discnum","method")
   discedvar = colnames(data[,-which(colnames(data) %in% discvar)])