update formula parameter description

R/discretization.R

@@ -41,7 +41,7 @@ st_unidisc = \(x,k,method = "quantile",factor = FALSE,
 #' @description
 #' Function for determining the best univariate discretization based on geodetector q-statistic.
 #'
-#' @param formula A formula of spatial stratified heterogeneity test.
+#' @param formula A formula of best univariate discretization.
 #' @param data A data.frame or tibble of observation data.
 #' @param discnum (optional) A vector of number of classes for discretization. Default is `3:15`.
 #' @param discmethod (optional) A vector of methods for discretization,default is using

R/gd_sesu.R

@@ -9,7 +9,7 @@
 #' analysis: Cases with different types of spatial data, GIScience & Remote Sensing, 57(5), 593-610.
 #' doi: 10.1080/15481603.2020.1760434.
 #'
-#' @param formula A formula.
+#' @param formula A formula of comparison of size effects of spatial units.
 #' @param datalist A list of \code{data.frame} or \code{tibble}.
 #' @param su A vector of sizes of spatial units.
 #' @param discvar Name of continuous variable columns that need to be discretized.Noted that

R/psd_spade.R

@@ -94,7 +94,7 @@ cpsd_spade = \(yobs,xobs,xdisc,wt){
 #' Xuezhi Cang & Wei Luo (2018) Spatial association detector (SPADE),International
 #' Journal of Geographical Information Science, 32:10, 2055-2075, DOI:  10.1080/13658816.2018.1476693
 #'
-#' @param formula A formula of spatial stratified heterogeneity test.
+#' @param formula A formula of calculate power of spatial and multilevel discretization determinant \eqn{PSMDQ_s}.
 #' @param data A data.frame or tibble of observation data.
 #' @param wt (optional) The spatial weight matrix.When `wt` is not provided, must provide `locations`.
 #' And gdverse will use `locations` columns to construct spatial weight use `inverse_distance_weight()`.
@@ -152,6 +152,7 @@ psmd_spade = \(formula,data,wt = NULL,locations = NULL,discnum = NULL,
 
   calcul_psmd = \(param){
     discm = param[[1]]
+    discn = param[[2]]
 
     if (discm == 'robust'){
 

R/robustdisc.R

@@ -4,7 +4,7 @@
 #' Determines discretization interval breaks using an optimization algorithm for variance-based
 #' change point detection.
 #'
-#' @param formula A formula of spatial stratified heterogeneity test.
+#' @param formula A formula of univariate discretization.
 #' @param data A data.frame or tibble of observation data.
 #' @param discnum A numeric vector of discretized classes of columns that need to be discretized.
 #' @param minsize (optional) The min size of each discretization group.Default all use `1`.