kernel_weights function

Distance-based Kernel Spatial Weights

Create a kernel weights by specifying a bandwidth and a kernel method

kernel_weights(
  sf_obj,
  bandwidth,
  kernel_method,
  use_kernel_diagonals = FALSE,
  power = 1,
  is_inverse = FALSE,
  is_arc = FALSE,
  is_mile = TRUE
)

Arguments

• sf_obj: An sf (simple feature) object
• bandwidth: A positive numeric value of bandwidth
• kernel_method: a string value, which has to be one of 'triangular', 'uniform', 'epanechnikov', 'quartic', 'gaussian'
• 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.

Returns

An instance of Weight-class

Examples

library(sf)
guerry_path <- system.file("extdata", "Guerry.shp", package = "rgeoda")
guerry <- st_read(guerry_path)
bandwidth <- min_distthreshold(guerry)
kernel_w <- kernel_weights(guerry, bandwidth, kernel_method = "uniform")
summary(kernel_w)