gdverse | Analysis of Spatial Stratified Heterogeneity • gdverse

Analysis of Spatial Stratified Heterogeneity

Overview

Current models and functions provided by gdverse are:

Model	Function	Support
GeoDetector	`geodetector()`	✔️
OPGD	`opgd()`	✔️
GOZH	`gozh()`	✔️
LESH	`lesh()`	✔️
SPADE	`spade()`	✔️
IDSA	`idsa()`	✔️
RGD	`rgd()`	✔️
RID	`rid()`	✔️
SRSGD	`srsgd()`	✔️

Installation

Install from CRAN with:

install.packages("gdverse", dep = TRUE)

Install development binary version from R-universe with:

install.packages('gdverse',
                 repos = c("https://stscl.r-universe.dev",
                           "https://cloud.r-project.org"),
                 dep = TRUE)

Install development source version from GitHub with:

# install.packages("devtools")
devtools::install_github("stscl/gdverse",
                         build_vignettes = TRUE,
                         dep = TRUE)

✨ Please ensure that Rcpp is properly installed and the appropriate C++ compilation environment is configured in advance if you want to install gdverse from github.

✨ The gdverse package supports the use of robust discretization for the robust geographical detector and robust interaction detector. For details on using them, please refer to https://stscl.github.io/gdverse/articles/rgdrid.html.

Example

library(gdverse)
data("ndvi")
ndvi
## # A tibble: 713 × 7
##    NDVIchange Climatezone Mining Tempchange Precipitation    GDP Popdensity
##         <dbl> <chr>       <fct>       <dbl>         <dbl>  <dbl>      <dbl>
##  1    0.116   Bwk         low         0.256          237.  12.6      1.45  
##  2    0.0178  Bwk         low         0.273          214.   2.69     0.801 
##  3    0.138   Bsk         low         0.302          449.  20.1     11.5   
##  4    0.00439 Bwk         low         0.383          213.   0        0.0462
##  5    0.00316 Bwk         low         0.357          205.   0        0.0748
##  6    0.00838 Bwk         low         0.338          201.   0        0.549 
##  7    0.0335  Bwk         low         0.296          210.  11.9      1.63  
##  8    0.0387  Bwk         low         0.230          236.  30.2      4.99  
##  9    0.0882  Bsk         low         0.214          342. 241       20.0   
## 10    0.0690  Bsk         low         0.245          379.  42.0      7.50  
## # ℹ 703 more rows

OPGD model

discvar = names(ndvi)[-1:-3]
discvar
## [1] "Tempchange"    "Precipitation" "GDP"           "Popdensity"
ndvi_opgd = opgd(NDVIchange ~ ., data = ndvi, 
                 discvar = discvar, cores = 6)
ndvi_opgd
## ***   Optimal Parameters-based Geographical Detector     
##                 Factor Detector            
## 
## |   variable    | Q-statistic | P-value  |
## |:-------------:|:-----------:|:--------:|
## | Precipitation |  0.8693505  | 2.58e-10 |
## |  Climatezone  |  0.8218335  | 7.34e-10 |
## |  Tempchange   |  0.3330256  | 1.89e-10 |
## |  Popdensity   |  0.1990773  | 6.60e-11 |
## |    Mining     |  0.1411154  | 6.73e-10 |
## |      GDP      |  0.1004568  | 3.07e-10 |

GOZH model

g = gozh(NDVIchange ~ ., data = ndvi)
g
## ***   Geographically Optimal Zones-based Heterogeneity Model       
##                 Factor Detector            
## 
## |   variable    | Q-statistic | P-value  |
## |:-------------:|:-----------:|:--------:|
## | Precipitation | 0.87255056  | 4.52e-10 |
## |  Climatezone  | 0.82129550  | 2.50e-10 |
## |  Tempchange   | 0.33324945  | 1.12e-10 |
## |  Popdensity   | 0.22321863  | 3.00e-10 |
## |    Mining     | 0.13982859  | 6.00e-11 |
## |      GDP      | 0.09170153  | 3.96e-10 |