robust geographical detector(RGD) model

Usage

rgd(
  formula,
  data,
  discvar = NULL,
  discnum = 3:8,
  minsize = 1,
  strategy = 2L,
  increase_rate = 0.05,
  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 3:8.
minsize: (optional) The min size of each discretization group. Default all use 1.
strategy: (optional) Optimal discretization strategy. When strategy is 1L, choose the highest q-statistics to determinate optimal spatial data discretization parameters. When strategy is 2L, The optimal discrete parameters of spatial data are selected by combining LOESS model.
increase_rate: (optional) The critical increase rate of the number of discretization. Default is 5%.
cores: (optional) Positive integer (default is 1). When cores are greater than 1, use multi-core parallel computing.

Value

A list.

factor: robust power of determinant
opt_disc: optimal robust discrete results
allfactor: factor detection results corresponding to different number of robust discreteizations
alldisc: all robust discrete results

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

data('sim')
# \donttest{
tryCatch({
    g = rgd(y ~ .,
           data = dplyr::select(sim,-dplyr::any_of(c('lo','la'))),
           discnum = 3:6, cores = 1)
    g
  }, error = \(e) message("Skipping Python-dependent example: ", e$message))
#> ***      Robust Geographical Detector    
#> 
#> | variable | Q-statistic |   P-value    |
#> |:--------:|:-----------:|:------------:|
#> |    xc    |  0.7011119  | 7.650000e-10 |
#> |    xb    |  0.6032094  | 1.186300e-08 |
#> |    xa    |  0.4969454  | 4.191848e-06 |
#> 
# }