Compute an array of simulation envelopes using a summary function that returns an array of curves.
envelopeArray(X, fun, ..., dataname = NULL, verb = FALSE, reuse = TRUE)An object of class "fasp" representing
an array of envelopes.
Object containing point pattern data.
A point pattern (object of class
"ppp", "lpp", "pp3" or "ppx")
or a fitted point process model
(object of class "ppm", "kppm" or "lppm").
Function that computes the desired summary statistic
for a point pattern. The result of fun should be a
function array (object of class "fasp").
Arguments passed to envelope to control the simulations,
or passed to fun when evaluating the function.
Optional character string name for the data.
Logical value indicating whether to print progress reports.
Logical value indicating whether the envelopes in each panel
should be based on the same set of simulated patterns
(reuse=TRUE, the default)
or on different, independent sets of simulated
patterns (reuse=FALSE).
Adrian Baddeley Adrian.Baddeley@curtin.edu.au, Rolf Turner r.turner@auckland.ac.nz and Ege Rubak rubak@math.aau.dk.
This command is the counterpart of envelope
when the function fun that is evaluated on each simulated point pattern
will return an object of class "fasp" representing an array of
summary functions.
Simulated point patterns are generated according to the
rules described for envelope. In brief,
if X is a point pattern, the algorithm generates
simulated point patterns of the same kind, according to complete
spatial randomness. If X is a fitted model, the algorithm
generates simulated point patterns according to this model.
For each simulated point pattern Y, the function fun
is invoked. The result Z <- fun(Y, ...) should be an object of
class "fasp" representing an array of summary functions.
The dimensions of the array Z should be the same
for each simulated pattern Y.
This algorithm finds the simulation envelope of the summary functions in each cell of the array.
envelope, alltypes.
if(interactive()) {
Nsim <- 19
X <- finpines
co <- "best"
} else {
## smaller task to reduce check time
Nsim <- 3
X <- finpines[c(FALSE, TRUE)]
co <- "none"
}
A <- envelopeArray(X, markcrosscorr, nsim=Nsim, correction=co)
plot(A)
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