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alltypes(X, fun="K", ..., dataname=NULL,verb=FALSE,envelope=FALSE)"ppp"."F", "G", "J", "K", "pcf",
"Gcross"<envelope if appropriate)plot.fasp() in forming the title verb is
true then terse ``progress reports'' (just the values of the
mark indices) are printed out when the calculations for that
combination of marks are completed.envelope is true, then simulation envelopes
of the summary function will also be computed. See Details."fasp",
see fasp.object). This can be plotted
using plot.fasp.If the pattern is not marked, the resulting ``array'' has dimensions $1 \times 1$. Otherwise the following is true:
If fun="F",
the function array has dimensions $m \times 1$
where $m$ is the number of different marks in the point pattern.
The entry at position [i,1] in this array
is the result of applying Fest to the
points of type i only.
If fun is "Gdot", "Jdot"
or "Kdot", the function array
again has dimensions $m \times 1$.
The entry at position [i,1] in this array
is the result of Gdot(X, i) or Jdot(X, i)
or Kdot(X, i) respectively.
If fun is "Gcross", "Jcross" or "Kcross",
(or their abbreviations "G", "J" or "K"),
the function array has dimensions $m \times m$.
The [i,j] entry of the function array
(for $i \neq j$) is the
result of applying the function Gcross,
Jcross or Kcross to
the pair of types (i,j). The diagonal
[i,i] entry of the function array is the result of
applying the univariate function Gest,
Jest or Kest to the
points of type i only.
If envelope=FALSE, then
each function entry fns[[i]] retains the format
of the output of the relevant estimating routine
Fest, Gest, Jest,
Kest, Gcross, Jcross, Kcross,
Gdot, Jdot, or Kdot.
The default formulae for plotting these functions are
cbind(km,theo) ~ r for F, G, and J functions, and
cbind(trans,theo) ~ r for K functions.
If envelope=TRUE, then each function entry fns[[i]]
has the same format as the output of the envelope command.
"fasp") amenable to plotting
by plot.fasp(). The argument fun specifies the summary function that will
be evaluated for each type of point, or for each pair of types.
It may be either an Rfunction or a character string.
Suppose that the points have possible types $1,2,\ldots,m$
and let $X_i$ denote the pattern of points of type $i$ only.
If fun="F" then this routine
calculates, for each possible type $i$,
an estimate of the Empty Space Function $F_i(r)$ of
$X_i$. See Fest
for explanation of the empty space function.
The estimate is computed by applying Fest
to $X_i$ with the optional arguments ....
If fun is
"Gcross", "Jcross" or "Kcross",
the routine calculates, for each pair of types $(i,j)$,
an estimate of the ``i-toj'' cross-type function
$G_{ij}(r)$,
$J_{ij}(r)$ or
$K_{ij}(r)$ respectively describing the
dependence between
$X_i$ and $X_j$.
See Gcross, Jcross
or Kcross respectively for explanation of these
functions.
The estimate is computed by applying the relevant function
(Gcross etc)
to X using each possible value of the arguments i,j,
together with the optional arguments ....
If fun is "pcf" the routine calculates
the cross-type pair correlation function pcfcross
between each pair of types.
If fun is
"Gdot", "Jdot" or "Kdot",
the routine calculates, for each type $i$,
an estimate of the ``i-to-any'' dot-type function
$G_{i\bullet}(r)$,
$J_{i\bullet}(r)$ or
$K_{i\bullet}(r)$ respectively describing the
dependence between $X_i$ and $X$.
See Gdot, Jdot
or Kdot respectively for explanation of these functions.
The estimate is computed by applying the relevant function
(Gdot etc)
to X using each possible value of the argument i,
together with the optional arguments ....
The letters "G", "J" and "K"
are interpreted as abbreviations for "Gcross", "Jcross"
and "Kcross" respectively, assuming the point pattern is
marked. If the point pattern is unmarked, the appropriate
function Fest, Jest
or Kest is invoked instead.
If envelope=TRUE, then as well as computing the value of the
summary function for each combination of types, the algorithm also
computes simulation envelopes of the summary function for each
combination of types. The arguments ... are passed to the function
envelope to control the number of
simulations, the random process generating the simulations,
the construction of envelopes, and so on.
plot.fasp,
fasp.object,
Fest,
Gest,
Jest,
Kest,
Gcross,
Jcross,
Kcross,
Gdot,
Jdot,
Kdot,
envelope.# bramblecanes (3 marks).
data(bramblecanes)
<testonly>bramblecanes <- bramblecanes[c(seq(1, 744, by=20), seq(745, 823, by=4))]</testonly>
bF <- alltypes(bramblecanes,"F",verb=TRUE)
plot(bF)
plot(alltypes(bramblecanes,"G"))
plot(alltypes(bramblecanes,"Gdot"))
# Swedishpines (unmarked).
data(swedishpines)
<testonly>swedishpines <- swedishpines[1:25]</testonly>
plot(alltypes(swedishpines,"K"))
plot(alltypes(swedishpines,"F"))
data(amacrine)
plot(alltypes(amacrine, "pcf"), ylim=c(0,1.3))
# A setting where you might REALLY want to use dataname:
xxx <- alltypes(ppp(Melvin$x,Melvin$y,
window=as.owin(c(5,20,15,50)),marks=clyde),
fun="F",verb=TRUE,dataname="Melvin")
# envelopes
bKE <- alltypes(bramblecanes,"K",envelope=TRUE,nsim=19)
bFE <- alltypes(bramblecanes,"F",envelope=TRUE,nsim=19,global=TRUE)
# extract one entry
as.fv(bKE[1,1])Run the code above in your browser using DataLab