r <- matrix(c(1,2,2,1), nrow=2,ncol=2)
MultiStrauss(r)
# prints a sensible description of itself
r <- 0.03 * matrix(c(1,2,2,1), nrow=2,ncol=2)
X <- amacrine
<testonly>X <- X[ owin(c(0, 0.8), c(0, 1)) ]</testonly>
ppm(X ~1, MultiStrauss(r))
# fit the stationary multitype Strauss process to `amacrine'
ppm(X ~polynom(x,y,3), MultiStrauss(r, c("off","on")))
# fit a nonstationary multitype Strauss process with log-cubic trend
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