| alltypes {spatstat} | R Documentation |
Given a marked point pattern, this computes the estimates of
a selected summary function (F,G, J or K)
of the pattern, for all possible combinations of marks.
It returns these functions in
a list (an object of class "fasp") amenable to plotting
by plot.fasp().
alltypes(pp, fun="K",dataname=NULL,verb=FALSE)
pp |
The observed point pattern, for which summary function
estimates are required. An object of class "ppp".
If the pattern is not marked, the resulting ``array'' has dimensions
1 x 1.
|
fun |
Character string indicating the summary function
required. Options are
"F", "G", "J", "K",
"Gcross", "Jcross", "Kcross",
"Gdot", "Jdot", "Kdot".
|
dataname |
Character string giving an optional (alternative)
name to the point pattern, different from what is given
in the call. This name, if supplied, may be used by
plot.fasp() in forming the title of the plot.
If not supplied it defaults to the parsing of the argument
supplied as pp in the call.
|
verb |
Logical value, meaning ``verbose''. If 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. |
This routine is a convenient way to analyse the dependence between types in a multitype point pattern. Suppose that the points have possible types 1,2,...,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.
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[i,j](r),
J[i,j](r) or
K[i,j](r) respectively describing the
dependence between
X[i] and X[j].
See Gcross, Jcross
or Kcross respectively for explanation of these functions.
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.](r),
J[i.](r) or
K[i.](r) respectively describing the
dependence between X[i] and X.
See Gdot, Jdot
or Kdot respectively for explanation of these functions.
The letters "G", "J" and "K"
are interpreted as abbreviations for "Gcross", "Jcross"
and "Kcross" respectively, assumin the point pattern is
marked. If the point pattern is unmarked, the appropriate
function Fest, Jest
or Kest is invoked instead.
A function array (an object of class "fasp",
see fasp.object). This can be plotted
using plot.fasp.
If fun="F",
the function array has dimensions m * 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 * 1.
The entry at position [i,1] in this array
is the result of Gdot(pp, i) or Jdot(pp, i)
or Kdot(pp, i) respectively.
If fun is "Gcross", "Jcross" or "Kcross",
(or their abbreviations "G", "J" or "K"),
the function array has dimensions m * m.
The [i,j] entry of the function array
(for i != 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.
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.
Sizeable amounts of memory may be needed during the calculation.
Adrian Baddeley adrian@maths.uwa.edu.au http://www.maths.uwa.edu.au/~adrian/ and Rolf Turner rolf@math.unb.ca http://www.math.unb.ca/~rolf
plot.fasp,
fasp.object,
allstats,
Fest,
Gest,
Jest,
Kest,
Gcross,
Jcross,
Kcross,
Gdot,
Jdot,
Kdot
# bramblecanes (3 marks).
data(bramblecanes)
## Not run:
X.F <- alltypes(bramblecanes,fun="F",verb=TRUE)
plot(X.F)
X.G <- alltypes(bramblecanes,fun="G",verb=TRUE)
X.J <- alltypes(bramblecanes,fun="J",verb=TRUE)
X.K <- alltypes(bramblecanes,fun="K",verb=TRUE)
X.Gd <- alltypes(bramblecanes,fun="Gdot",verb=TRUE)
X.Jd <- alltypes(bramblecanes,fun="Jdot",verb=TRUE)
X.Kd <- alltypes(bramblecanes,fun="Kdot",verb=TRUE)
## End(Not run)
# Swedishpines (unmarked).
data(swedishpines)
X.K <- alltypes(swedishpines,fun="K")
X.F <- alltypes(swedishpines,fun="F")
X.G <- alltypes(swedishpines,fun="G")
X.J <- alltypes(swedishpines,fun="J")
# simulated data
## Not run:
pp <- runifpoint(350, owin(c(0,1),c(0,1)))
pp$marks <- factor(c(rep(1,50),rep(2,100),rep(3,200)))
X.F <- alltypes(pp,fun="F",verb=TRUE,dataname="Fake Data")
X.G <- alltypes(pp,fun="G",verb=TRUE,dataname="Fake Data")
X.J <- alltypes(pp,fun="J",verb=TRUE,dataname="Fake Data")
X.K <- alltypes(pp,fun="K",verb=TRUE,dataname="Fake Data")
## End(Not run)
# A setting where you might REALLY want to use dataname:
## Not run:
xxx <- alltypes(ppp(Melvin$x,Melvin$y,
window=as.owin(c(5,20,15,50)),marks=clyde),
fun="F",verb=TRUE,dataname="Melvin")
## End(Not run)