owin to create the window, if window is missing
so it is taking ``owin1'' in your call to be an argument to be passed to as.owin
(which confuses the living Drambuie out of it), rather than being the window
argument.
Do:
ppp1 <- ppp(lidar[,1],lidar[,2],window=owin1)
an
27;
cheers,
Rolf Turner
P. S. The ``name=value'' way of specifying function arguments in R
is very powerful but takes a little getting used to.
R. T.
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e(U$bdry[[1]][1:2])
> V <- V[!duplicated(V),]
> U$bdry[[1]][1:2] <- V
> # Check:
> plot(rotate(U))
Well, the workaround works in this toy example. Who knows what pitfalls
lurk in more complicated settings?
cheers,
Rolf Turner
pley", verbose=FALSE)
# 3. No errors or warnings occur; plot the result:
plot(res)
If you have not yet been able to resolve your problems, perhaps you
could provide a data set which demonstrates these problems.
cheers,
Rolf Turner
On 13/01/2011, at 7:35 AM, Karthik
uced within envelope() will be
patterns on the window corresponding to ``intens'' which
is in turn the window of ``landscape''. It doesn't really
make sense to compare the (inhomogeneous) K function of
a pattern living in window W_1 with those of patterns living
Try setting:
spatstat.options(gpclib=TRUE)
You would have found out about this if you'd done
licence.polygons()
as the start-up message from spatstat suggests.
cheers,
Rolf Turner
P. S. The help on spatstat.options() says that gpclib defaul
and so point
pattern analysis doesn't come into it.
It may be the case that some sort of combination of kriging and time
series
or repeated measures analysis might be called for. But here I speak of
that of which I know nothing.
cheers,
Rolf Turner
__
precisely just what problems you are trying to
solve.
cheers,
Rolf Turner
On Thu, Feb 10, 2011 at 3:42 PM, Rolf Turner
wrote:
On 11/02/2011, at 6:00 AM, david depew wrote:
Dear list,
A brief and (hopefully) simplistic question regarding point patte
n the ***anticlockwise*** direction, and the last point should
***not*** repeat
the first. Then do
W <- owin(poly=DF)
HTH.
cheers,
Rolf Turner
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ols is required.
Let me know if you are interested and I can give you detailed
instructions
as to how to do the fitting together.
cheers,
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???
?inside.owin
cheers,
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;centroid")
if(is.null(angle)) angle <- runif(1,-pi/2,pi/2)
U <- rotate(U,angle)
shift(U,vec=unlist(centroid.owin(W)))
}
Check:
SQ <- unit.square()
plot(owin(c(-1,2),c(-1,2)),main="")
plot(SQ,add=TRUE)
plot(foo(SQ),add=TRUE,border="red")
plot(foo(SQ,a
methodology that invokes the usual theory will be invalid for your
patterns.
If you are not invoking any such methodology, then go for it.
If you don't like getting the warnings, then you could use
suppressWarnings()
cheers,
Rolf Turner
On 07/04/11 23:27, francesco wrote
free to nudge me about it, from time to time! :-)
cheers,
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consistent
with your modelling criteria.
Note that the distmap() and distfun() functions in "spatstat" will allow
you to determine the
distance from a given point to the nearest road (if the roads are
represented as "psp"
objects).
cheers,
Rolf Turner
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source of errors. See
fortune("dog").
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dinates
is confusing and counterintuitive. See fortune("conventions").
No ``fix'' is needed.
cheers,
Rolf Turner
On 18/05/11 05:21, Robin W Hunnewell wrote:
> Dear R-sig Geo people,
> I've run a quadrat.test on a "ppp" object, for
$r
The function K3est() does not have an "r" argument. Note that
the argument "r" to envelope gets passed, as part of the "..."
arguments.
Try
xxx <- K3est(X,rmax=73,nrval=1001)
and look at xxx$r; this might be what you want.
cheers,
Rolf Turner
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.
To change this behaviour, execute
spatstat.options(gpclib=TRUE)
cheers,
Rolf Turner
On 24/05/11 04:10, Mathieu Rajerison wrote:
> Hi,
>
>
> I have a set of points.
>
> I generated two different sets of ppp objets, each with a different window
> (but same points)
>
&
uot;Spatial" Task View on CRAN
for some other possibilities, including "splancs" and "spatial".
cheers,
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t the model that you wish
to simulate?
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surely *not* the right thing to do.
However you could try it, since it would be very easy to implement,
and see what it tells you. You might thereby get some insight into
how to define the distance measure properly.
cheers,
Rolf Turner
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es the same result as
above.
Does this accomplish your objectives?
cheers,
Rolf Turner
On 08/06/11 17:32, mattc0 wrote:Hi R-sig-geo'ers
I am attempting to generate an image with each pixel showing the euclidean
distance to nearest line feature using spatstat.
I would lik
tools
explicitly designed for this sort of thing.
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"planar segment pattern") object; the function (method)
as.linnet.psp() can then be used to turn the "psp" object into a
"linnet" object.
HTH
cheers,
Rolf Turner
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counties come into the picture? You said you wanted to get
the road distance between points on the roads. What have the counties
got to do with this?
Can you perhaps provide a reproducible example?
cheers,
Rolf
El jue., 20 de jun. de 2019 a la(s) 19:08, Rolf Turner
(r.tur...@auckland.ac.nz
he counties involved? Is n the number of counties?
Are you interested in the road distance (minimum road distance?) between
pairs of counties?
Please explain *clearly* and do not expect those who are trying to help
you to be mind-readers!!!
cheers,
Rolf
El sáb., 22 de jun. de 2019 a
it seems that you
want something rather different, and it's still not clear what.
You need to get *your* thoughts clear; make some definitions and
specifications, and decide what you really want or need.
It seems that you are expecting R to magically do your thinking for you;
it won
And to respond to
Juan Pablo's hope, nothing whatever is "bothering" me.
cheers,
Rolf
El sáb., 22 de jun. de 2019 a la(s) 21:15, Rolf Turner
(r.tur...@auckland.ac.nz <mailto:r.tur...@auckland.ac.nz>) escribió:
On 23/06/19 3:30 PM, Rolando Valdez wrote:
u cannot diagnose the problem, please send me a reprex and I will
look into it.
cheers,
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")
This test (not surprisingly) rejects the hypothesis that the intensities
are the same; p-value = 0.0020.
If this is not the hypothesis that you are interested in, please clarify
your thinking and your question, and get back to us.
cheers,
Rolf Turner
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On 25/07/19 12:50 PM, ASANTOS wrote:
Thanks for your help Marcelino e for the careful explanation Rolf Turner
and so sorry about my post script configuration, I expected that I
solved that in my new post.
First my variable area is a marked point (attribute or auxiliary
information about
h
question(s), is unclear to me and is likely to be complicated.
cheers,
Rolf
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[1] Spatial Point Patterns: Methodology and Applications with R
1st Edition, Adrian Baddeley, Ege Rubak, Rol
ind of
overwhelmed with work at the moment, so it may be a while till you hear
from him.
If you provide a reproducible example I *may* be able to help.
cheers,
Rolf Turner
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Dear Joe,
Further to my previous response to your post: I have now been in touch
with Adrian Baddeley and he has confirmed that the problem is as I
conjectured: The patterns in "pp_list" need to be compatible with
"xx". The error message was a bit misleading. (Adrian has now adjusted
t
On 26/09/19 8:52 AM, Rodrigo Plei wrote:
Dear colleagues,
How to I specify latitude and longitude intervals on x and y axis in a map
using the maptools package?
Suppose that I plotted a map and using the argument "axes = TRUE", I got
the y (latitude) axis plotted to show "-23.6 -23.4 -23.2 -
Sorry for the noise. I'm just trying to test a message filter on my mailer.
cheers,
Rolf Turner
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were not read by the loop. The codes are given below
Perhaps use try()???
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copyright by
making it available in this way?
Could get you into trouble.
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hoops\n!") else cat("\nAlright!\n")
When I run this code, "Alright!" is duly echoed.
Printing "chk" gives "Time difference of 46 days" and 'chk > 365"
produces FALSE.
What happens when you run this code? Look at today, rv, rdat
ensity(), because
this will screw up the discretisation procedure.
We are very sceptical about the validity of applying clustering to the
elements of the discretisation.
HTH
cheers,
Rolf Turner
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On 17/07/20 9:04 pm, Michal Kvasnička wrote:
Dear Rolf.
Thanks a lot for the suggestions! I'll check it out.
Best wishes to you and all spatstat team,
*Ing. Michal Kvasnička, Ph.D.*
Good luck with your endeavours. I'd like to point out a slight glitch
in the advice that I proffered, exp
My apologies for the noise. Please ignore this message.
I am just trying to test out message filters in a new mail client that
I am learning to use.
Again, sorry for the noise.
cheers,
Rolf Turner
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On Thu, 27 Aug 2020 21:17:58 -0400
ASANTOS via R-sig-Geo wrote:
> Dear R-Sig_Geo Members,
>
> I'd like to find a more simple way to filtering a set of points in a
> "ppp" object by minimum or maximum distance.
>
> In my example using a ants ("ppp" object) in spatstat package:
>
> #Packages
yourself. (As in the popular epithet "Go
unsubscribe yourself! :-) ) No-one can do it for you! :-)
See (click on) the link above and then scroll to the bottom of the page
and click on the "Unsubscribe or edit options" button.
cheers,
Rolf Turner
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De
On Wed, 10 Feb 2021 16:40:50 +
Barry Rowlingson wrote:
> Before messing with lgcp I'd look at spatstat - lgcp is more intended
> for relative risk calculations where you have "cases" and "controls",
> and also for
> space-time data.
>
> spatstat seems to have functions for fitting (and sim
strive to avoid such usage.
Again let me express the hope that you won't take offence at this
comment.
cheers,
Rolf Turner
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k says: "If you just want to unsubscribe from this
list, click on the Unsubscribe button and a confirmation message will
be sent to you."
cheers,
Rolf Turner
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Phone:
ing what relrisk() does, i.e.
# using a ratio of intensities.
r4 <- fhat/ghat
# Now view the results.
plot(anylist(risk=r1,risk.raw=r2,relrisk=r3,
relrisk.raw=r4),nrows=2,main="")
All is in harmony! OMM!
Hope this helps.
cheers,
Rolf Turner
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t to reinforce what Roger Bivand has already told you (with
admirable clarity) --- the expression that you give above is for the
*square* of the (Pearson) residual, not the actual residual.
cheers,
Rolf Turner
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Stats.
.owin() to the three results. (Again, if my
guess is correct, this may not work.)
Adrian or Ege may be able to propose a more efficient/effective solution.
cheers,
Rolf Turner
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" equal to sigma,
and cov(X,Y) = 0). Consequently the units of sigma are the units in
which X and Y are measured.
Thus if, for example, your point coordinates are in metres, then the
units of sigma are metres. (So sigma is measured not in area but in
length or distance.)
HTH
cheers,
Rolf Turner
On 23/02/16 10:34, Tadaishi Yatabe-Rodriguez wrote:
Thanks, Rolf. This ,makes it clearer. I've another question though: the
ppp object I get the Kernel density from is not projected, then what
would be the unit of projection of this un-projected object? The
projection of the object from which it
nd "y" are *reserved* names. You cannot use these names
for any covariates *other than* the Cartesian coordinates.
(5) The name "covariate" is probably *not* a good name for a covariate.
As fortune(77) puts it "Would you call your dog 'dog'?"
(6) Likewise (and
On 07/04/16 19:52, Virginia Morera Pujol wrote:
Hi Rolf,
Thank you for your very complete response. If I understand it correctly
then, I should just include the Cartesian coordinates in my covariates
list if I want to model the intensity specifically in relation to them
as well as the covariates
t the given locations --- say, stored as k
This is interpreted as meaning that (x_i,y_i) is the centroid of the
i-th region, in which count k_i was obtained.
If so, can you not just calculate:
xc <- sum(k*x)/sum(k)
yc <- sum(k*y)/sum(k)
???
What am I not understanding?
cheers,
g
E <- alltypes(amacrine, Kcross, nsim=19, envelope=TRUE, global=FALSE)
Thanks,
Try:
E <- envelope(amacrine, Kcross, funargs=list(i="on",j="off"),
nsim=19,global=FALSE)
cheers,
Rolf Turner
P. S. Note that you *do not need* to set "global=FALSE
t 128 (e.g.1024 or 2048) in the calls to disc().
cheers,
Rolf Turner
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#==
library(spatstat)
bdry <-
On 26/05/16 00:23, ASANTOS wrote:
Dear Rolf Turner,
It's much better a clean code with a minimum packages, thank
you very much for your answer. But "pct" object give me a total polygon
percentage around each point and I need too an identification (in
columns
E". The object T is
over-writeable (whereas TRUE is not!) and this can lead on occasion to
mysterious errors accompanied by incomprehensible error messages.
cheers,
Rolf Turner
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P
.
It's hard to tell for sure without a *reproducible example* (!!!). We
don't have access to Data.ppp.
Try using alternative="greater" in your call to dclf.test() and see if
the results are more in keeping with your expectations.
cheers,
Rolf Turner
--
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ded earlier:
dclf.test(Data.ppp,Kcross, i = "A", j = "D", alternative="greater" ,correction =
"border")
dclf.test(Data.ppp,Kcross, i = "B", j = "D", alternative="greater" ,correction =
"border")
dclf.test(Data.ppp
this kind of data?
The spatstat package has facilities for dealing with *spatial* point
processes on geometric networks. I am not aware of any work for dealing
with spatio-temporal processes on such networks.
cheers,
Rolf Turner
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Universi
ed(42)
X <- rpoispp(100)
plot(allstats(X))
This ran with no problem, and produced the expected plot.
(e) The function to estimate the J function is Jest(). It has been in
the spatstat package for a very long time.
cheers,
Rolf Turner
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Depa
pacing <= 0.00586
I attached the data for you to investigate. Thanks a lot.
Thank you for providing the data. There does indeed seem to be a
problem. We are looking into it.
cheers,
Rolf Turner
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om github.
cheers,
Rolf Turner
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On 05/10/16 21:29, Cenk İÇÖZ wrote:
Dear Rolf,
I installed the fixed version of spatstat from github repository.
allstats and Jest worked perfectly.
Thanks for all the help. I will be waiting for the new version
release. Many thanks for the package and contributions to the point
pattern analysi
ines(100,L)
plot(W,main="Piras's Polygon")
plot(X,add=TRUE)
Note that I have just generated 100 uniform points, r.t. 1000, so that
the resulting plot is a little less cluttered.
There may be a sexier way of accomplishing your desideratum; I have
cc-ed this email to my co-authors Adr
xs[xs < 1] <- xs[xs < 1] + 99
xs[xs > 100] <- xs[xs > 100] - 99
X$data$x[marks(X)=="p"] <- xp
X$data$x[marks(X)=="s"] <- xs
X
}
E <- envelope(X,fun=linearpcfcross,i="s",j="p",
simulate=expression(fo
above, or better still read the (even more incredibly well
written :-) ) book to which you can find a pointer by pointing your
browser at http://spatstat.github.io.
That's about all I can say in response to such a general question. If
you have further focussed and specific question
.
Better to use return(as.vector(z)). See fortune(185).
cheers,
Rolf Turner
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https
On 26/01/17 00:01, Nicolas Fabre wrote:
This is not the way you unsubscribe. See the list info (given at the
bottom of every posting).
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ed) "owin" object you would run the risk of incurring this
"jumping" phenomenon. Hence it would be safer to bundle your collection
of polygons into a list, and apply rjitter() to each list entry (using
lapply()).
cheers,
Rolf Turner
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to it. How can I do this in R?
The project2segment() function from the spatstat package will probably
do what you want.
cheers,
Rolf Turner
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2 hectares you would take their sides to be of length 402.0673
metres.
cheers,
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On 04/03/17 08:38, Marcelino de la Cruz Rot wrote:
Hi Manuel,
I do answer to the question "How can I make a spatial grid of 1 ha (or
other size) in R?"
You can use function hextess in spatstat
library(spatstat)
# some arbitrary area, with coordinates in hectometres
W <- Window(chorley)
# A
On 05/03/17 01:35, Marcelino de la Cruz Rot wrote:
My apologies for such a pair (or more) of embarrassing mistakes!
I should read a bit more these days...
I'm just happy to see that this sort of mistake happens to others as
well as to my very good self! :-)
cheers,
Rolf
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fitted is an ill-determined creature and the bandwidth that gives the
best fit is even more ill-determined.
cheers,
Rolf Turner
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siduals.ppm to specify the fitted
intensity values.
fit2 <- ppm(X ~ 1, forcefit=TRUE)
res <- residuals(fit2, fittedvalues=lam[quad.ppm(fit2)])
cheers,
Rolf Turner
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nceptually a
special case of "polygonal" but has (obviously?) practical advantages
when it is applicable.
However an "owin" object *cannot* be a combination of polygonal and mask
types.
cheers,
Rolf Turner
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s=15,centre=c(673593.21,673593.21),npoly=8)
Does that provide (at least a start on) what you want?
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Rolf Turner
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Whoops. I cc-ed my message to r-help rather than to r-sig-geo. (Du!)
Consequently I'm resending, with r-sig-geo as a cc recipient.
cheers,
Rolf Turner
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On 13/09/17 19:37,
0.801,1.6]
[0.5,1]35 39
[0,0.5)42 36
Is this something like what you wish to achieve?
cheers,
Rolf Turner
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__
On 13/09/17 11:08, Guy Bayegnak wrote:
Thanks a lot for your response and suggestion Rolf. Yes, by "quadrant" I mean
the little sub-windows. My problem is the following:
We have collected thousands of groundwater samples across a vast area, and analysed them.
Based on the analysis we are abl
On 30/10/17 09:55, Sergio Ibarra wrote:
Dear list members,
How to split lines at vertices with sf?
Huh?
I know they say brevity is the soul of wit, but I think that this
posting carries that idea a bit too far.
cheers,
Rolf Turner
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(tol = 0.001, component
1)
Could you please suggest any idea to solve this problem?
This question is not appropriate for R-sig-Geo. You should have sent it
to R-sig-mixed-models.
cheers,
Rolf Turner
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ion (March 2013)
I am cc-ing to the man himself to see if he has further comment.
cheers,
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Finally:
set.seed(42)
X <- runifpoint(20,win=test.window)
xxx <- ppm(X ~ test.im)
plot(residuals(xxx))
# No sign of any missing values.
cheers,
Rolf Turner
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u an answer, even though it's a crappy answer.
Although, I have one predictor that is a continuous distfun, and
I get the same error message from rhohat with that.
Don't think that I can come up with any useful suggestions as to how to
proceed from here. Sorry.
cheers,
Rolf Turner
your task.
Can you provide a minimal reproducible example of your situation, with a
clear explanation of what you want to do next? Some subscribers to
r-sig-geo (myself *not* included) are very clever, but few if any are
telepathic.
cheers,
Rolf Turner
--
Technical Editor ANZJS
Department
ation window, not
just at the points of the observed pattern.
See
Adrian Baddeley, Ege Rubak, Rolf Turner (2015). Spatial Point
Patterns: Methodology and Applications with R. London: Chapman and
Hall/CRC Press, 2015. URL
http://www.crcpress.com/Spatial-Point-Patterns-Methodology-and-Applica
You have a new question, so start a new thread with an
appropriate subject line.
I shall shortly attempt to answer your question in such a new thread.
cheers,
Rolf Turner
--
Technical Editor ANZJS
Department of Statistics
University of Auckland
Phone: +64-9-373-7599 ext.
ei, Z=bei.extra$elev, M=M,
pch=".", col=col.pts, cex=1.25)
HTH
cheers,
Rolf Turner
--
Technical Editor ANZJS
Department of Statistics
University of Auckland
Phone: +64-9-373-7599 ext. 88276
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ht
On 06/05/18 05:31, Raja Natarajan wrote:
hyperspectral astrology images
Did you mean *astronomy* ??? !!!
I certainly hope so! :-)
cheers,
Rolf Turner
--
Technical Editor ANZJS
Department of Statistics
University of Auckland
Phone: +64-9-373-7599 ext. 88276
ease re-post your question en anglais, if you can. You are
much more likely to get a useful answer if you do. Bon chance.
Cordialement,
Rolf Turner
--
Technical Editor ANZJS
Department of Statistics
University of Auckland
Phone: +64-9-373-7599 ext. 88276
___
by converting your polygons to "owin"
objects.
cheers,
Rolf Turner
--
Technical Editor ANZJS
Department of Statistics
University of Auckland
Phone: +64-9-373-7599 ext. 88276
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ion
that would split the original polygons into "onlyA", "onlyB" and
"AintersectingB" polygons?
You can do this easily in spatstat by converting your polygons to "owin"
objects.
cheers,
Rolf Turner
--
Technical Editor ANZJS
Department of Statistics
Uni
of class "owin". The
as.owin() function should handle this for you.
cheers,
Rolf Turner
--
Technical Editor ANZJS
Department of Statistics
University of Auckland
Phone: +64-9-373-7599 ext. 88276
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R-sig-Geo@r-proj
On 1/13/19 1:06 AM, Roger Bivand wrote:
... GWR is very demanding for computation. It should only ever be used
for exploring model mis-specification, never for inference or prediction.
So making a bad test on a bad method run faster should not be a priority.
Fortune nomination!
cheers,
Ro
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