[R-sig-Geo] A simple correlogram using sp.correlogram with data(meuse)

[Michael Treglia]

Just to follow up, I corresponded with the author of pgirmess (Patrick
Giraudoux), and he committed the necessary changes in the correlog function
to CRAN
(updated version of pgirmess is 1.6.0)
http://cran.r-project.org/web/packages/pgirmess/index.html

[if you have trouble getting it through CRAN yet, updated versions of
source or compiled package is available here:
http://giraudoux.pagesperso-orange.fr/]

Best,
Mike

On Tue, Apr 28, 2015 at 1:46 PM, Michael Treglia <mtreglia at gmail.com> wrote:

> Thanks Roger! That solves it.
> Best,
> Mike
>
> On Tue, Apr 28, 2015 at 12:49 PM, Roger Bivand <Roger.Bivand at nhh.no>
> wrote:
>
>> On Tue, 28 Apr 2015, Michael Treglia wrote:
>>
>>  Hi all,
>>>
>>> This is a bit a tangential to the question, but related to
>>> pgirmess::correlog used in this thread, so I thought it appropriate to
>>> follow-up here [if not, apologies - I can start a new thread if that's
>>> preferred].
>>>
>>> In recent exploration with the pgirmess::correlog, I was unable to change
>>> the alternative hypothesis being tested. Since pgirmess::correlog uses
>>> spdep::moran.test, the alternative hypothesis being tested is by default
>>> "greater" (confirmed in the documentation). The help for the function
>>> indicates pgirmess::correlog should also be able to take arguments from
>>> 'moran.test' within it. Thus, users should be able to use the
>>> 'alternative'
>>> argument to change the alternative hypothesis being tested.  When trying
>>> to
>>> use "alternative='less'" (or 'two.sided'), an error is returned:
>>>
>>> Error in try(moran.test(lst.z1[[i]], nb2listw(lst.nb1[[i]], style =
>>> "W")),
>>> :
>>>  unused argument (alternative = "less")
>>>
>>
>> The problem is that the ... is passed to try(), not moran.test() or
>> geary.test() in:
>>
>> xt <- switch(pmatch(method, c("Moran", "Geary"), nomatch = 3),
>>     try(moran.test(lst.z1[[i]], nb2listw(lst.nb1[[i]],
>>         style = "W")), silent = TRUE, ...), try(geary.test(lst.z1[[i]],
>>         nb2listw(lst.nb1[[i]], style = "W")), silent = TRUE,
>>         ...), stop("Method must be 'Moran' or 'Geary'"))
>>
>> With:
>>
>> xt <- switch(pmatch(method, c("Moran", "Geary"), nomatch = 3),
>>     try(moran.test(lst.z1[[i]], nb2listw(lst.nb1[[i]],
>>         style = "W"), ...), silent = TRUE), try(geary.test(lst.z1[[i]],
>>         nb2listw(lst.nb1[[i]], style = "W"), ...), silent = TRUE),
>>         stop("Method must be 'Moran' or 'Geary'"))
>>
>> via for example correlog1 <- edit(correlog), it works. You can save the
>> function for later use too.
>>
>> Hope this helps,
>>
>> Roger
>>
>>
>>
>>
>>> Reproducible Code (based on the example from help for
>>> pgirmess::correlog):
>>>
>>> library(spdep)
>>> library(pgirmess)
>>> data(oldcol)
>>> attach(COL.OLD)
>>> coords<-cbind(X,Y)
>>> res<-correlog(coords,CRIME, method="Moran",
>>> nbclass=NULL,alternative="less")
>>> ## Error in try(moran.test(lst.z1[[i]], nb2listw(lst.nb1[[i]], style =
>>> "W")),  :
>>> ##  unused argument (alternative = "less")
>>>
>>> I corresponded with the author of pgirmess and he did not have a solution
>>> nor much time to work on it. I was hoping to give a go at
>>> trouble-shooting
>>> myself, but haven't had a chance, so this thread seemed like a relevant
>>> place to bring up the issue, so others are at least aware of it.
>>>
>>> Best,
>>> Mike Treglia
>>>
>>>
>>>
>>>
>>>
>>>
>>> On Tue, Apr 28, 2015 at 2:05 AM, Roger Bivand <Roger.Bivand at nhh.no>
>>> wrote:
>>>
>>>  On Tue, 28 Apr 2015, Andy Bunn wrote:
>>>>
>>>>  Hi all, This seems trivial easy but being a bear of very little
>>>> brain...
>>>>
>>>>>
>>>>> I'm looking to build a correlogram using Moran's I and the function
>>>>> sp.correlogram() with data(meuse) as a SpatialPointsDataFrame. I've
>>>>> done
>>>>> so with the ncf library using correlog() but getting the equivalent
>>>>> out of
>>>>> library sp is eluding me. Can somebody help me out?
>>>>>
>>>>>
>>>> require(ncf)
>>>> ncf.cor <- ncf::correlog(x=coordinates(meuse)[,1],
>>>>  y=coordinates(meuse)[,2], z=meuse$zinc, increment=200, resamp=100)
>>>>
>>>> ncf::correlog() chooses bins based on increment. Alternatively,
>>>> pgirmess::correlog() uses by default an optimal number of bins, but can
>>>> use
>>>> a bin count:
>>>>
>>>> library(pgirmess)
>>>> pgir.cor <- pgirmess::correlog(coordinates(meuse), z=meuse$zinc,
>>>> "Moran",
>>>>   nbclass=23)
>>>> plot(pgir.cor[,1], pgir.cor[,2], type="b")
>>>> cbind(pgir.cor[,1], ncf.cor$mean.of.class)
>>>> cbind(pgir.cor[,4], ncf.cor$n)
>>>>
>>>> The differences come from ncf::correlog() constructing the spatial
>>>> weights
>>>> itself, while pgirmess::correlog() uses spdep::dnearneigh() to construct
>>>> them for the distance bins and then spdep::nb2listw() and
>>>> spdep::moran.test() internally in a loop, once for each bin.
>>>>
>>>> spdep::sp.correlogram() follows the original Cliff & Ord understanding
>>>> of
>>>> a spatial correlogram - like time series lags - of order 1, order 2,
>>>> etc.
>>>> The input spatial weights define the weighted graph, so order 2
>>>> neighbours
>>>> are neighbours of order 1 neighbours by stepping out on the graph.
>>>> pgirmess::correlog() was written to use distance rather than graph edge
>>>> count distance:
>>>>
>>>> library(spdep)
>>>> nb200 <- dnearneigh(meuse, 0, 200)
>>>> spdep.cor <- spdep::sp.correlogram(nb200, meuse$zinc, order=23,
>>>>  method="I", zero.policy=TRUE)
>>>> plot(spdep.cor)
>>>>
>>>> To get the implied mean distances for lags of nb200:
>>>>
>>>> nb200_23 <- nblag(nb200, 23)
>>>> mdbins <- sapply(nb200_23, function(x) mean(unlist(nbdists(x, meuse))))
>>>> mdbins
>>>>
>>>> There are two different understandings of this spatial correlogram, the
>>>> C&O one based on time series and counting distance in graph edges, and
>>>> another using distance bands, also found in globalG.test, etc.
>>>>
>>>> Hope this clarifies,
>>>>
>>>> Roger
>>>>
>>>>
>>>>
>>>>  -Andy
>>>>>
>>>>> require(sp)
>>>>> require(ncf)
>>>>> data(meuse)
>>>>> coordinates(meuse) <- ~x+y
>>>>> proj4string(meuse) <- CRS("+init=epsg:28992")
>>>>> ncf.cor <- correlog(x=coordinates(meuse)[,1], y=coordinates(meuse)[,2],
>>>>> z=meuse at data$zinc, increment=200, resamp=100)
>>>>>
>>>>> _______________________________________________
>>>>> R-sig-Geo mailing list
>>>>> R-sig-Geo at r-project.org
>>>>> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
>>>>>
>>>>>
>>>>>  --
>>>> Roger Bivand
>>>> Department of Economics, Norwegian School of Economics,
>>>> Helleveien 30, N-5045 Bergen, Norway.
>>>> voice: +47 55 95 93 55; fax +47 55 95 91 00
>>>> e-mail: Roger.Bivand at nhh.no
>>>>
>>>>
>>>> _______________________________________________
>>>> R-sig-Geo mailing list
>>>> R-sig-Geo at r-project.org
>>>> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
>>>>
>>>>
>>>
>> --
>> Roger Bivand
>> Department of Economics, Norwegian School of Economics,
>> Helleveien 30, N-5045 Bergen, Norway.
>> voice: +47 55 95 93 55; fax +47 55 95 91 00
>> e-mail: Roger.Bivand at nhh.no
>>
>>
>

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