Hi,
My coordinates geographical are decimal degrees. I am soryy I donot know how to
and what do copy and paste from SAM to gwr()? I cannot see the code of SAM.
Thanks a lot.
Cheers.
ÔÚ2010-05-13 17:43:06£¬"Roger Bivand" <roger.biv...@nhh.no> дµÀ£º
>On Thu, 13 May 2010, huangykiz wrote:
>
>> Hi,
>
>> I am sorry I say that I cannot get the same R^2 between in R/spgwr and
>> SAM in my data.
>
>Establish that the adaptive proportion is exactly the same.
>
>You haven't done that - copy and paste from SAM to gwr(), not using
>gwr.sel(). Do it first for fixed Gaussian, then if you get a sensible
>figure from SAM for adaptive, do the same there. I see very different
>bandwidths chosen by SAM and by gwr.sel() and GWR3 - gwr.sel() and GWR3
>usually agree fairly well for CV fixed bandwidths, but gwr.sel() typically
>continues its search a little longer than GWR3.
>
>I don't know how SAM chooses its bandwidth or adaptive proportion, it is
>closed source, so only its authors know.
>
>Is SAM using Great Circle distances, if so, you should set longlat=TRUE in
>gwr.sel() and gwr()? Are your coordinates geographical (decimal degrees)
>or projected (metres)?
>
>Roger
>
>> In R/spgwr
>> R^2: 0.972989;
>> AICc (GWR p. 61, eq 2.33; p. 96, eq. 4.21): 4668.92
>> Effective number of parameters (model: traceS): 435.7586;
>> Effective number of parameters (residual: 2traceS - traceS'S): 582.3581;
>> Sigma (residual: 2traceS - traceS'S): 2.437066;
>> Sigma (model: traceS): 1.927127;
>> Sigma (ML): 1.325501;
>>
>> In SAM,
>> Coefficient of Determination : 0.696
>> Adjusted r-square (r?Adj): 0.693
>> Sigma: 20.058
>> Effective Number of Parameters: 10.002
>> Akaike Information Criterion (AICc): 4838.299
>> Correlation Coefficient (r): 0.834
>> F: 207.852
>>
>> Here are my code:
>> PET.adapt.gauss <- gwr.sel(SPECIES_RI ~ PET, data=Environmental_variables,
>> coords=cbind(Environmental_variables$LONGX,
>> Environmental_variables$LATY),adapt=TRUE)
>>
>> PET.gauss<- gwr(SPECIES_RI ~ PET, data=Environmental_variables,
>> coords=cbind(Environmental_variables$LONGX,
>> Environmental_variables$LATY),
>> gweight=gwr.Gauss,adapt=PET.adapt.gauss,hatmatrix=TRUE)
>>
>> 1 -
>> (PET.gauss$results$rss/crossprod(scale(Environmental_variables$SPECIES_RI,
>> scale=FALSE)))
>>
>> In SAM, I selecte "spatial Weighting Function"=gaussian, adaptive
>> Spatial Kernel, and compute Geographical Distances based on longitudinal
>> coordinate(X) and latitudinal coordinate(Y). I donot select method for
>> AIC optimisation.
>>
>> So I donot know where is wrong.
>>
>> Thank you very much for your great helps.
>>
>>
>>
>>
>>
>>
>> ÔÚ2010-05-13 00:07:23£¬"Roger Bivand" <roger.biv...@nhh.no> дµÀ£º
>>> On Wed, 12 May 2010, Roger Bivand wrote:
>>>
>>>> On Wed, 12 May 2010, huangykiz wrote:
>>>>
>>>>> Hi, Is "adapt=TRUE"(spgwr) not the same as "adaptive Spatial
>>>>> Kernel"(SAM)?The result of "adaptive Spatial Kernel" may be better than
>>>>> fixed bandwidth. If I want to ues "adaptive Spatial Kernel" in spgwr, how
>>>>> to write the code?
>>>>
>>>> READ THE HELP PAGES!
>>>>
>>>> adaptive_proportion <- gwr.sel(...)
>>>>
>>>> result <- gwr(..., adapt=adaptive_proportion; ...)
>>>>
>>>> exactly as on the example om the help page:
>>>>
>>>> data(georgia)
>>>> g.adapt.gauss <- gwr.sel(PctBach ~ TotPop90 + PctRural + PctEld + PctFB +
>>>> PctPov + PctBlack, data=gSRDF, adapt=TRUE)
>>>> res.adpt <- gwr(PctBach ~ TotPop90 + PctRural + PctEld + PctFB + PctPov +
>>>> PctBlack, data=gSRDF, adapt=g.adapt.gauss)
>>>> res.adpt
>>>>
>>>> Clear?
>>>
>>> I have now compared the same data in R/spgwr and SAM for effective number
>>> of parameters, sigma, and your questionable R^2, and they agree adequately
>>> when the kernel and the bandwidth are the same. Having the algorithm
>>> choose the bandwidth does obscure what is going on. You should use SAM if
>>> you prefer GUI and not needing to know how things work, and remember that
>>> GWR is a very doubtful approach for anything beyond exploring
>>> non-stationarity, its original motivation.
>>>
>>>>
>>>>>
>>>>> Thanks a lot.
>>>>>
>>>>> Cheers.
>>>>>
>>>>>
>>>>>> Hi,
>>>>>> I think that I use the same bandwidth and kernel. In SAM, I use "spatial
>>>>>> Weighting Function"=gaussian, adaptive Spatial Kernel, and compute
>>>>>> Geographical Distances based on longitudinal coordinate(X) and
>>>>>> latitudinal
>>>>>> coordinate(Y). In spgwr, gweight is gwr.Gauss and adapt is TRUE.
>>>>>>
>>>>>> For example, this is my code:
>>>>>
>>>>>> PET.bw <- gwr.sel(SPECIES_RI ~ PET, data=variables,
>>>>>> coords=cbind(variables$LONGX, variables$LATY),adapt=TRUE)
>>>>>
>>>>>> PET.gauss <- gwr(SPECIES_RI ~ PET, data=variables,
>>>>>> coords=cbind(variables$LONGX, variables$LATY), bandwidth=PET.bw,
>>>>>> gweight=gwr.Gauss,adapt=TRUE,hatmatrix=TRUE)
>>>>>
>>>>> So where do you pass PET.bw to the gwr() function? adapt=TRUE will treat
>>>>> the adaptive proportion as 1, so include all data points. If you want to
>>>>> compare, use a fixed bandwidth in both, with no CV selection. Then you
>>>>> compare like with like.
>>>>>
>>>>> Note that your messages are *not* reaching the list, they must be sent to:
>>>>>
>>>>> r-sig-geo@stat.math.ethz.ch, not
>>>>>
>>>>> r-sig-geo-requ...@stat.math.ethz.ch
>>>>>
>>>>> You are not thinking carefully and are rushing into things and drawing
>>>>> wrong conclusions.
>>>>>
>>>>>>
>>>>>> Thanks a lot.
>>>>>>
>>>>>> Cheers.
>>>>>>
>>>>>>
>>>>>>
>>>>>> ÔÚ2010-05-12 20:28:47£¬"Roger Bivand" <roger.biv...@nhh.no> дµÀ£º
>>>>>>> On Wed, 12 May 2010, huangykiz wrote:
>>>>>>>
>>>>>>>> Hi,
>>>>>>>> One of SAM author ("Jos¨¦ Alexandre Felizola Diniz
>>>>>>>> Filho"<di...@icb.ufg.br>) say that they also base on GWR3 (the
>>>>>>>> Fotherigham book) and the data used within each kernel may be some
>>>>>>>> slight differences
>>>>>>>
>>>>>>> Naturally, if you are not using exactly the same kernel and bandwidth,
>>>>>>> you should not be surprised by differences in values. Please make sure
>>>>>>> that the bandwidth and kernel are the same and try again.
>>>>>>>
>>>>>>> Roger
>>>>>>>
>>>>>>>> Cheers
>>>>>
>>>>>
>>>>>
>>>>>
>>>>> ÔÚ2010-05-12 20:28:47£¬"Roger Bivand" <roger.biv...@nhh.no> дµÀ£º
>>>>>> On Wed, 12 May 2010, huangykiz wrote:
>>>>>>
>>>>>>> Hi,
>>>>>>> One of SAM author ("Jos¨¦ Alexandre Felizola Diniz
>>>>>>> Filho"<di...@icb.ufg.br>) say that they also base on GWR3 (the
>>>>>>> Fotherigham book) and the data used within each kernel may be some
>>>>>>> slight differences
>>>>>>
>>>>>> Naturally, if you are not using exactly the same kernel and bandwidth,
>>>>>> you
>>>>>> should not be surprised by differences in values. Please make sure that
>>>>>> the bandwidth and kernel are the same and try again.
>>>>>>
>>>>>> Roger
>>>>>>
>>>>>>> Cheers.
>>>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>> ÔÚ2010-05-12 15:27:58£¬"Roger Bivand" <roger.biv...@nhh.no> дµÀ£º
>>>>>> On Wed, 12 May 2010, huangykiz wrote:
>>>>>>
>>>>>>> Hi,
>>>>>>>
>>>>>>> I am sorry I donot know how to install module spgwr from sourceforge (I
>>>>>>> can find it on the web
>>>>>>> http://r-spatial.cvs.sourceforge.net/viewvc/r-spatial/spgwr/R/gwr.R?view=log).
>>>>>>>
>>>>>>> So I use the code sketch to calculate quasi-global R2. The results are
>>>>>>> different between SAM and spgwr(Attached are the results ). The
>>>>>>> quasi-global R2 in R is 0.4515894, but in SAM is 0.696.
>>>>>>> This is my code:
>>>>>>>
>>>>>>> library(spgwr)
>>>>>>> Environmental_variables<-read.csv("Environmental_variables100.csv",header=TRUE)
>>>>>>> attach(Environmental_variables)
>>>>>>> region_PET.bw <- gwr.sel(SPECIES_RI ~ PET,
>>>>>>> data=Environmental_variables,
>>>>>>> coords=cbind(Environmental_variables$LONGX,
>>>>>>> Environmental_variables$LATY),adapt=TRUE)
>>>>>>> region_PET.gauss <- gwr(SPECIES_RI ~ PET, data=Environmental_variables,
>>>>>>> coords=cbind(Environmental_variables$LONGX,
>>>>>>> Environmental_variables$LATY), bandwidth=region_PET.bw,
>>>>>>> gweight=gwr.Gauss,adapt=TRUE,hatmatrix=TRUE)
>>>>>>> names(region_PET.gauss$SDF)
>>>>>>> region_PET.gauss$SDF$localR2
>>>>>>> 1 -
>>>>>>> (region_PET.gauss$results$rss/crossprod(scale(Environmental_variables$SPECIES_RI,
>>>>>>>
>>>>>>> scale=FALSE)))
>>>>>>>
>>>>>>> Thank you very much.
>>>>>>
>>>>>> SAM is closed source - ask them how they compute it. For spgwr, the code
>>>>>> is provided, so you can read it for yourself. For the record, the
>>>>>> current
>>>>>> gwr() code in spgwr gives the same value as GWR3, which is also closed
>>>>>> source, and where the Effective number of parameters (model: traceS),
>>>>>> Sigma, and Residual sum of squares also agree. I suppose SAM has a
>>>>>> different understanding of GWR internals than the authors of the GWR
>>>>>> book.
>>>>>>
>>>>>> Once again:
>>>>>>
>>>>>> Please *do* write to the R-sig-geo list rather than to me directly -
>>>>>> others can answer your question as well, perhaps better, and in a more
>>>>>> timely way than I can. In addition, threads in the list can be searched
>>>>>> in
>>>>>> the archives, so others can avoid the same problem later.
>>>>>>
>>>>>> Please summarise to the list if this resolves the problem.
>>>>>>
>>>>>> Roger
>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> ÔÚ2010-05-12 01:16:18£¬"Roger Bivand" <roger.biv...@nhh.no> дµÀ£º
>>>>>>>> On Wed, 12 May 2010, huangykiz wrote:
>>>>>>>>
>>>>>>>>> Hi, I just need one for global, not *each* fit point. In this case,
>>>>>>>>> how
>>>>>>>>> can I select or do? Why in other software such as SAM(Spatial
>>>>>>>>> Analysis
>>>>>>>>> in Macroecology) just gives one R2?
>>>>>>>>
>>>>>>>> If you believe theirs, good luck! The authors of the GWR book have
>>>>>>>> local
>>>>>>>> R^2 values in GWR3 and formulae that are wrong by their own admission
>>>>>>>> in
>>>>>>>> private emails. The localR2 now agrees with the as-yet unreleased GWR4
>>>>>>>> from the GWR authors. How SAM can be "better", I don't know. What you
>>>>>>>> are suggesting is that the model fitted with fit points at data points
>>>>>>>> (but not at other fit points) might have a "quasi-global" R^2, based
>>>>>>>> on
>>>>>>>> the RSS of the pooled fit. For the columbus case, that might be:
>>>>>>>>
>>>>>>>> 1 - (col.gauss$results$rss/crossprod(scale(columbus$crime,
>>>>>>>> scale=FALSE)))
>>>>>>>>
>>>>>>>> but I don't know whether this is in any way correct. I've added it as:
>>>>>>>>
>>>>>>>> Quasi-global R2:
>>>>>>>>
>>>>>>>> to the print output of a GWR model fitted with a hatmatrix, and have
>>>>>>>> committed it to sourceforge, project r-spatial, module spgwr.
>>>>>>>> Arguably,
>>>>>>>> it ought to be adjusted by the ratio of degrees of freedom, but I
>>>>>>>> don't
>>>>>>>> trust the DF either. Could you please check out spgwr from sourceforge
>>>>>>>> ,install it from source, and confirm that the "quasi-global R2" does
>>>>>>>> the
>>>>>>>> same as SAM, or use the code sketch above to do the same, and report
>>>>>>>> back?
>>>>>>>>
>>>>>>>> Roger
>>>>>>>>
>>>>>>>>>
>>>>>>>>> Thanks a lot.
>>>>>>>>>
>>>>>>>>> Cheers,
>>>>>>>>>
>>>>>>>>>
>>>>>>>>>
>>>>>>>>>
>>>>>>>>>
>>>>>>>>> ÔÚ2010-05-11 23:59:44£¬"Roger Bivand" <roger.biv...@nhh.no> дµÀ£º
>>>>>>>>>> On Tue, 11 May 2010, huangykiz wrote:
>>>>>>>>>>
>>>>>>>>>>> Hi,
>>>>>>>>>>>
>>>>>>>>>>> There are 49 localR2 in the results. Which one do I need? The code
>>>>>>>>>>> "look for localR2:" cannot run.
>>>>>>>>>>
>>>>>>>>>> Well, how many do you want? There is one for each fit point, they
>>>>>>>>>> are
>>>>>>>>>> *local* R2. Please do try to grasp what GWR does - it fits one
>>>>>>>>>> moddel
>>>>>>>>>> for *each* fit point.
>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>> Thans a lot
>>>>>>>>>>>
>>>>>>>>>>> Cheers.
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>>
>>>>>>>>>>> ÔÚ2010-05-11 22:33:59£¬"Roger Bivand" <roger.biv...@nhh.no> дµÀ£º
>>>>>>>>>>>> On Tue, 11 May 2010, huangykiz wrote:
>>>>>>>>>>>>
>>>>>>>>>>>>> Hi, OK. But I need it for compariation. In what some contexts to
>>>>>>>>>>>>> get it? May you tell me how to get it?
>>>>>>>>>>>>
>>>>>>>>>>>> library(spgwr)
>>>>>>>>>>>> data(columbus)
>>>>>>>>>>>> col.bw <- gwr.sel(crime ~ income + housing, data=columbus,
>>>>>>>>>>>> coords=cbind(columbus$x, columbus$y))
>>>>>>>>>>>> col.gauss <- gwr(crime ~ income + housing, data=columbus,
>>>>>>>>>>>> coords=cbind(columbus$x, columbus$y), bandwidth=col.bw,
>>>>>>>>>>>> hatmatrix=TRUE)
>>>>>>>>>>>> names(col.gauss$SDF)
>>>>>>>>>>>>
>>>>>>>>>>>> look for localR2:
>>>>>>>>>>>>
>>>>>>>>>>>> col.gauss$SDF$localR2
>>>>>>>>>>>>
>>>>>>>>>>>> But do not rely on it or use it for anything at all! Like all GWR,
>>>>>>>>>>>> it is most unreliable!
>>>>>>>>>>>>
>>>>>>>>>>>> Roger Bivand
>>>>>>>>>>>>
>>>>>>>>>>>>>
>>>>>>>>>>>>> Thank you very much for your great helps
>>>>>>>>>>>>>
>>>>>>>>>>>>> Best regards.
>>>>>>>>>>>>>
>>>>>>>>>>>>>
>>>>>>>>>>>>>
>>>>>>>>>>>>>
>>>>>>>>>>>>>
>>>>>>>>>>>>> ÔÚ2010-05-11 18:28:44£¬"Roger Bivand" <roger.biv...@nhh.no> дµÀ£º
>>>>>>>>>>>>>> On Tue, 11 May 2010, huangykiz wrote:
>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> Dear professor Bivand,
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> I am a strudent. I recently use GWR(Geographically weighted
>>>>>>>>>>>>>>> regression) model. May I ask you a question? There is not
>>>>>>>>>>>>>>> Coefficient of Determination in the results of GWR. How can I
>>>>>>>>>>>>>>> get
>>>>>>>>>>>>>>> it? What is the programs to get it?
>>>>>>>>>>>>>>
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> Please address questions like this to the R-sig-geo list rather
>>>>>>>>>>>>>> than to me directly in future.
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> The local R2 values are available in some contexts when running
>>>>>>>>>>>>>> gwr(), but are not well defined (neither in the GWR book nor in
>>>>>>>>>>>>>> implementations). I advise against their use - they are most
>>>>>>>>>>>>>> probably meaningless.
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> Hope this helps,
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> Roger Bivand
>>>>>>>>>>>>>>
>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> Thank you very much for your any helps.
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> Best regards.
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> Yong Huang
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> --
>>>>>>>>>>>>>> Roger Bivand
>>>>>>>>>>>>>> Economic Geography Section, Department of Economics, Norwegian
>>>>>>>>>>>>>> School of
>>>>>>>>>>>>>> Economics and Business Administration, Helleveien 30, N-5045
>>>>>>>>>>>>>> Bergen,
>>>>>>>>>>>>>> Norway. voice: +47 55 95 93 55; fax +47 55 95 95 43
>>>>>>>>>>>>>> e-mail: roger.biv...@nhh.no
>>>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>> --
>>>>>>>>>>>> Roger Bivand
>>>>>>>>>>>> Economic Geography Section, Department of Economics, Norwegian
>>>>>>>>>>>> School of
>>>>>>>>>>>> Economics and Business Administration, Helleveien 30, N-5045
>>>>>>>>>>>> Bergen,
>>>>>>>>>>>> Norway. voice: +47 55 95 93 55; fax +47 55 95 95 43
>>>>>>>>>>>> e-mail: roger.biv...@nhh.no
>>>>>>>>>>
>>>>>>>>>> --
>>>>>>>>>> Roger Bivand
>>>>>>>>>> Economic Geography Section, Department of Economics, Norwegian
>>>>>>>>>> School
>>>>>>>>>> of
>>>>>>>>>> Economics and Business Administration, Helleveien 30, N-5045 Bergen,
>>>>>>>>>> Norway. voice: +47 55 95 93 55; fax +47 55 95 95 43
>>>>>>>>>> e-mail: roger.biv...@nhh.no
>>>>>>>>
>>>>>>>> --
>>>>>>>> Roger Bivand
>>>>>>>> Economic Geography Section, Department of Economics, Norwegian School
>>>>>>>> of
>>>>>>>> Economics and Business Administration, Helleveien 30, N-5045 Bergen,
>>>>>>>> Norway. voice: +47 55 95 93 55; fax +47 55 95 95 43
>>>>>>>> e-mail: roger.biv...@nhh.no
>>>>>>
>>>>>> --
>>>>>> Roger Bivand
>>>>>> Economic Geography Section, Department of Economics, Norwegian School of
>>>>>> Economics and Business Administration, Helleveien 30, N-5045 Bergen,
>>>>>> Norway. voice: +47 55 95 93 55; fax +47 55 95 95 43
>>>>>> e-mail: roger.biv...@nhh.no
>>>>
>>>>
>>>
>>> --
>>> Roger Bivand
>>> Economic Geography Section, Department of Economics, Norwegian School of
>>> Economics and Business Administration, Helleveien 30, N-5045 Bergen,
>>> Norway. voice: +47 55 95 93 55; fax +47 55 95 95 43
>>> e-mail: roger.biv...@nhh.no
>
>--
>Roger Bivand
>Economic Geography Section, Department of Economics, Norwegian School of
>Economics and Business Administration, Helleveien 30, N-5045 Bergen,
>Norway. voice: +47 55 95 93 55; fax +47 55 95 95 43
>e-mail: roger.biv...@nhh.no
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