calc_dist_kernel: Calculates the spatial kernel values

In qleclerc/epicspatial: Flexible Spatial Modelling of Epidemics

Description

Calculates the spatial kernel values between all areas in a spatial dataset using their distance and population. This uses a gravity kernel structure (either matched or smooth depending on the threshold distance).

Usage

calc_dist_kernel(dist_mat, dist_c, spatial_data, alpha, p, p2, aa,
  delta = 0.3)

Arguments

dist_mat	The distance matrix between all areas.
dist_c	The threshold distance for the matched kernel. Note that setting this to an extremely high value will effectively make the gravity kernel a smooth kernel with a single function since the threshold distance will never be crossed.
spatial_data	The spatial dataset containing the population data
alpha	The destination population power.
p	The distance power.
p2	The secondary distance power for the matched kernel.
aa	The offset distance.
delta	The home cell modifier (to compensate the distance within cells equal to 0).

Value

Returns one matrix object containing the spatial kernel values.

Examples

#Create a spatial dataset:
test_data = raster(nrow=10, ncol=10, xmn=1, xmx=100000, ymn=1, ymx=100000)
values(test_data) = runif(100, 1, 1000)

#Calculate distance matrix
dist_mat = calc_dist_mat(test_data)

dist_kernel = calc_dist_kernel(dist_mat, dist_c = 87, test_data, alpha=0.95, p=6.6, p2=1.53, aa=35)

qleclerc/epicspatial documentation built on May 21, 2019, 4:06 a.m.