(For internally use and test only) K-NN Kernel Spatial Weights

Create a kernel weights by specifying k-nearest neighbors and a kernel method

gda_kernel_knn_weights(
  geoda_obj,
  k,
  kernel_method,
  adaptive_bandwidth = TRUE,
  use_kernel_diagonals = FALSE,
  power = 1,
  is_inverse = FALSE,
  is_arc = FALSE,
  is_mile = TRUE
)

Arguments

geoda_obj

An instance of geoda

k

a positive integer number for k-nearest neighbors

kernel_method

a string value, which has to be one of 'triangular', 'uniform', 'epanechnikov', 'quartic', 'gaussian'

adaptive_bandwidth

(optional) TRUE (default) or FALSE: TRUE use adaptive bandwidth calculated using distance of k-nearest neithbors, FALSE use max distance of all observation to their k-nearest neighbors

use_kernel_diagonals

(optional) FALSE (default) or TRUE, apply kernel on the diagonal of weights matrix

power

(optional) The power (or exponent) of a number says how many times to use the number in a multiplication.

is_inverse

(optional) FALSE (default) or TRUE, apply inverse on distance value

is_arc

(optional) FALSE (default) or TRUE, compute arc distance between two observations

is_mile

(optional) TRUE (default) or FALSE, convert distance unit from mile to km.

Value

An instance of Weight-class

Examples

if (FALSE) { # \dontrun{
guerry_path <- system.file("extdata", "Guerry.shp", package = "rgeoda")
guerry <- geoda_open(guerry_path)
adptkernel_w = gda_kernel_knn_weights(guerry, 6, "uniform")
summary(adptkernel_w)
} # }