power of spatial and multilevel discretization determinant(PSMD) and the corresponding pseudo-p value

Function for calculate power of spatial and multilevel discretization determinant and the corresponding pseudo-p value.

Usage

psmd_pseudop(
  yobs,
  xobs,
  wt,
  discnum = 3:8,
  discmethod = "quantile",
  cores = 1,
  seed = 123456789,
  permutations = 0,
  ...
)

Arguments

yobs: Variable Y
xobs: The original undiscretized covariable X.
wt: The spatial weight matrix.
discnum: (optional) Number of multilevel discretization. Default will use 3:8.
discmethod: (optional) The discretization 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.
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().

Value

A tibble of power of spatial and multilevel discretization determinant and the corresponding pseudo-p value.

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

Author

Wenbo Lv lyu.geosocial@gmail.com

Examples

data('sim')
wt = sdsfun::inverse_distance_swm(sf::st_as_sf(sim,coords = c('lo','la')))
psmd_pseudop(sim$y,sim$xa,wt)
#> # A tibble: 1 × 2
#>   `Q-statistic` `P-value`        
#>           <dbl> <chr>            
#> 1         0.310 No Pseudo-P Value