rgd {gdverse} | R Documentation |
Function for robust geographical detector(RGD) model.
rgd(
formula,
data,
discvar,
discnum = NULL,
minsize = NULL,
cores = 1,
type = "factor",
alpha = 0.95
)
formula |
A formula of RGD model. |
data |
A data.frame or tibble of observation data. |
discvar |
Name of continuous variable columns that need to be discretized. Noted that
when |
discnum |
A numeric vector of discretized classes of columns that need to be discretized.
Default all |
minsize |
(optional) The min size of each discretization group. Default all use |
cores |
(optional) Positive integer(default is 1). If cores > 1, use |
type |
(optional) The type of geographical detector, which must be |
alpha |
(optional) Specifies the size of confidence level. Default is |
A list of the RGD model result.
factor
the result of factor detector
interaction
the result of interaction detector
risk
the result of risk detector
ecological
the result of ecological detector
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.
Wenbo Lv lyu.geosocial@gmail.com
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.
## Not run:
## The following code needs to configure the Python environment to run:
data('ndvi')
g = rgd(NDVIchange ~ ., data = ndvi, discvar = names(ndvi)[-1:-3],
cores = 6, type =c('factor','interaction'))
## End(Not run)