基于R语言地理探测器包（GD）空间异质性与驱动力分析

导入要分析的数据，并用切片器选择因变量和自变量，因变量在左侧，并删除无关数据，包括索引。

testdata <- read.csv(csvfile, header = TRUE, sep = ",")testdata=testdata[3:9]

输入可供选择的分类方法

#3 approaches to calculate disgress.discmethod <- c("equal","natural","quantile")

输入可供选择的分类基本数量

#classify 4~6discitv <- c(4:6)

筛选连续的自变量

#continuous variablescontinuous_variable <- colnames(testdata)[-1]

运行gdm函数

#gdm functiontestgdm <- gdm(WSI ~ .,continuous_variable = continuous_variable ,data = testdata,discmethod = discmethod, discitv = discitv)

分析结果

完整代码

Sys.setlocale(category = 'LC_CTYPE', locale = 'C')#This is for using in pycharm.library(GD)filepath <- "E:/BaiduNetdiskDownload/Driving/Yl_naturalBreaks/"setwd(filepath)#Change the workspacetemp=list.files(path=filepath,pattern="*.csv")#list csvfilenames in workspacefor( csvfile in temp){print(csvfile)testdata <- read.csv(csvfile, header = TRUE, sep = ",")#load datatestdata <- read.csv(".csv", header = TRUE, sep = ",")testdata=testdata[3:9]#5 approach to calculate disgress.discmethod <- c("equal","natural","quantile")#select the best one among automatically 3 approaches of discrizetion #classify 4~6 automaticallydiscitv <- c(4:6)#continuous independent variables' name listcontinuous_variable <- colnames(testdata)[-1] #[-1] is for unselect dependent variable #gdm functiontestgdm <- gdm(WSI ~ .,continuous_variable = continuous_variable ,data = testdata,discmethod = discmethod, discitv = discitv)#dependent variable is WSI}print(testgdm)}

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