robust geographical detector(RGD) model

Function for robust geographical detector(RGD) model.

Usage

rgd(formula, data, discvar = NULL, discnum = 3:22, minsize = 1, cores = 1)

Arguments

formula: A formula of RGD model.
data: A data.frame, tibble or sf object of observation data.
discvar: Name of continuous variable columns that need to be discretized. Noted that when formula has discvar, data must have these columns. By default, all independent variables are used as discvar.
discnum: A numeric vector of discretized classes of columns that need to be discretized. Default all discvar use 3:22.
minsize: (optional) The min size of each discretization group. Default all use 1.
cores: (optional) Positive integer (default is 1). When cores are greater than 1, use multi-core parallel computing.

Value

A list.

factor: the result of RGD model
disc: robust discrete results

Note

Please set up python dependence and configure GDVERSE_PYTHON environment variable if you want to run rgd(). See vignette('rgdrid',package = 'gdverse') for more details.

References

Zhang, Z., Song, Y.*, & Wu, P., 2022. Robust geographical detector. International Journal of Applied Earth Observation and Geoinformation. 109, 102782. DOI: 10.1016/j.jag.2022.102782.

Author

Wenbo Lv lyu.geosocial@gmail.com

Examples

if (FALSE) { # \dontrun{
## The following code needs to configure the Python environment to run:
data('ndvi')
g = rgd(NDVIchange ~ ., data = ndvi,
        discvar = names(ndvi)[-1:-3],
        discnum = 3:8, cores = 6)
} # }