
Given a point pattern X
and a spatial object Y
,
compute estimates of Foxall's
Gfox(X, Y, r=NULL, breaks=NULL, correction=c("km", "rs", "han"), W, ...)
Jfox(X, Y, r=NULL, breaks=NULL, correction=c("km", "rs", "han"), W, ...,
warn.trim=TRUE)
A function value table (object of class "fv"
)
which can be printed, plotted, or converted to a data frame of values.
A point pattern (object of class "ppp"
)
from which distances will be measured.
An object of class "ppp"
, "psp"
or "owin"
to which distances will be measured. Alternatively a pixel image
(class "im"
) with logical values.
Optional. Numeric vector. The values of the argument
This argument is for internal use only.
Optional.
The edge correction(s) to be used to estimate
"none"
, "rs"
, "km"
, "cs"
and "best"
.
Alternatively correction="all"
selects all options.
Optional. A window (object of class "owin"
)
to be taken as the window of observation.
The distribution function will be estimated from data inside W
.
The default is W=Frame(Y)
when Y
is a window,
and W=Window(Y)
otherwise.
Extra arguments affecting the discretisation of distances.
These arguments are ignored by Gfox
, but
Jfox
passes them to Hest
to determine
the discretisation of the spatial domain.
Logical value indicating whether a warning should be issued
by Jfox
when the window of X
had to be trimmed
in order to be a subset of the frame of Y
.
Rob Foxall and Adrian Baddeley Adrian.Baddeley@curtin.edu.au
Given a point pattern X
and another spatial object Y
,
these functions compute two nonparametric measures of association
between X
and Y
, introduced by Foxall
(Foxall and Baddeley, 2002).
Let the random variable X
to the object Y
.
Foxall's
Let the random variable Y
. The cumulative distribution function
of Hest
.
Foxall's
Accuracy of Jfox
depends on the pixel resolution,
which is controlled by the
arguments eps
, dimyx
and xy
passed to
as.mask
. For example, use eps=0.1
to specify
square pixels of side 0.1 units, and dimyx=256
to specify a
256 by 256 grid of pixels.
Foxall, R. and Baddeley, A. (2002) Nonparametric measures of association between a spatial point process and a random set, with geological applications. Applied Statistics 51, 165--182.
Gest
,
Hest
,
Jest
,
Fest
X <- copper$SouthPoints
Y <- copper$SouthLines
G <- Gfox(X,Y)
J <- Jfox(X,Y, correction="km")
# \testonly{
J <- Jfox(X,Y, correction="km", eps=1)
# }
Run the code above in your browser using DataLab