ExpDistMat {SDPDmod} | R Documentation |
Exponential distance matrix
Description
This function calculates the (negative) exponential distance matrix, with a given cutoff distance and a positive exponent value.
Usage
ExpDistMat(distMat, distCutOff = NULL, expn = 0.01, mevn = FALSE)
Arguments
distMat |
distance matrix |
distCutOff |
cutoff distance. Default = the maximal value from the distance matrix. |
expn |
positive exponent, default = 0.01 |
mevn |
logical, default FALSE. If TRUE, max-eigenvalue normalization is performed. |
Details
W is an nxn matrix with elements w_{ij}
, i, j = 1,..n, where
w_{ij}=e^{-\alpha d_{ij}}
, if 0 <= d_{ij} < D
and
w_{ij}=0
, if d_{ij} > D
or i = j
.
D is the distance cutoff point (maximum radius of influence),
d_{ij}
is the distance between spatial units i and j, and
\alpha
is the positive exponent (e.g. \alpha
= 0.01, 0.02,...).
Value
W |
spatial weights matrix (Default, not normalized) |
Author(s)
Rozeta Simonovska
Examples
data(gN3dist) ##distance in meters
W1 <- ExpDistMat(distMat = gN3dist, distCutOff = 100000)
dist2 <- gN3dist/1000 ##in km
W2 <- ExpDistMat(distMat = dist2, distCutOff = 100, expn = 0.02)
W2nor <- ExpDistMat(distMat = dist2, 100000, 0.001, mevn = TRUE)
[Package SDPDmod version 0.0.5 Index]