gdverse (version 1.3-1)

spade: spatial association detector (SPADE) model

Description

Function for spatial association detector (SPADE) model.

Usage

spade(
  formula,
  data,
  wt = NULL,
  discvar = NULL,
  discnum = 3:8,
  discmethod = "quantile",
  cores = 1,
  seed = 123456789,
  permutations = 0,
  ...
)

Value

A list.

factor

the result of SPADE model

Arguments

formula

A formula of spatial association detector (SPADE) model.

data

A data.frame, tibble or sf object of observation data.

wt

(optional) The spatial weight matrix. When data is not an sf object, must provide wt.

discvar

(optional) 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

(optional) Number of multilevel discretization. Default will use 3:8.

discmethod

(optional) The discretization methods. Default all use quantile. Note that when using different discmethod for discvar, please ensure that the lengths of both are consistent. Noted that robust will use robust_disc(); rpart will use rpart_disc(); Others use sdsfun::discretize_vector().

cores

(optional) Positive integer (default is 1). When cores are greater than 1, use multi-core parallel computing.

seed

(optional) Random number seed, default is 123456789.

permutations

(optional) The number of permutations for the PSD computation. Default is 0, which means no pseudo-p values are calculated.

...

(optional) Other arguments passed to sdsfun::discretize_vector(),robust_disc() or rpart_disc().

Author

Wenbo Lv

References

Xuezhi Cang & Wei Luo (2018) Spatial association detector (SPADE),International Journal of Geographical Information Science, 32:10, 2055-2075, DOI: 10.1080/13658816.2018.1476693

Examples

data('sim')
sim1 = sf::st_as_sf(sim,coords = c('lo','la'))
g = spade(y ~ ., data = sim1)
g