Test the spatial heterogeneity in data based on permutation.

Usage

spatial_hetero_test(
  x,
  coords,
  ...,
  resample = 5000,
  poly = 2,
  bw = 10,
  kernel = c("bisquared", "gaussian"),
  verbose = 0
)

Arguments

x: A matrix of data to be tested. Each column is a variable.
coords: A matrix of coordinates.
...: Additional arguments.
resample: The total times of resampling with replacement. Default to 5000.
poly: The number of polynomial terms used by the polynomial estimator. Default to 2.
bw: The adaptive bandwidth used by the polynomial estimator. Default to 10.
kernel: The kernel function used by the polynomial estimator.
verbose: The verbosity level. Default to 0.

Value

A shgt object of permutation-test results with the following items:

vars: The names of variables.
t0: The value of the statistics (variance of density estimation) on original values.
t: The value of the same statistics on permuted values.
p: The p-value for each variable.

Examples

data(multisampling.large)
spatial_hetero_test(multisampling.large$beta, multisampling.large$coords)
#> Spatial Heterogeneity Test
#> 
#>                  t0                   t Pr(t>t0)    
#> Intercept  0.081540 [0.031470,0.239609] 0.778200    
#> g1        29.266000 [1.045108,6.264079] 0.000000 ***
#> g2        21.339481 [0.759496,4.698393] 0.000000 ***
#> z1         0.110370 [0.034536,0.213022] 0.298600    
#> x1         0.000000 [0.000000,0.000000] 0.000000 ***
#> 
#> 
#> Significance levels: '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' '
#>