gdverse (version 1.3-3)

psmd_spade: power of spatial and multilevel discretization determinant(PSMD)

Description

Function for calculate power of spatial and multilevel discretization determinant PSMDQ_s.

Usage

psmd_spade(
  yobs,
  xobs,
  wt,
  discnum = 3:8,
  discmethod = "quantile",
  cores = 1,
  seed = 123456789,
  ...
)

Value

A value of power of spatial and multilevel discretization determinant PSMDQ_s.

Arguments

yobs

Variable Y

xobs

The original continuous covariable X.

wt

The spatial weight matrix.

discnum

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

discmethod

(optional) The discretize methods. Default will use quantile. If discmethod is set to robust, the function robust_disc() will be used. Conversely, if discmethod is set to rpart, the rpart_disc() function will be used. Others use sdsfun::discretize_vector(). Currently, only one discmethod can be used at a time.

cores

(optional) A positive integer(default is 1). If cores > 1, use parallel computation.

seed

(optional) Random seed number, default is 123456789.

...

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

Author

Wenbo Lv

Details

The power of spatial and multilevel discretization determinant formula is \(PSMDQ_s = MEAN(Q_s)\)

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')
wt = sdsfun::inverse_distance_swm(sf::st_as_sf(sim,coords = c('lo','la')))
psmd_spade(sim$y,sim$xa,wt)