[R-sig-Geo] geoR -- bins in experimental semivariogram

[Paulo Justiniano Ribeiro Jr]

Gema

the varigram distances are gruped in classes (simular to what is done with 
an histogram) and for each class the average semiveriance is computed

geoR like many other software/packages have a default option
(13 variogram points in geoR - probabily because this was written of 
friday.... ;)  )
You can however change this to other specification which may be
more appropriate for your data.

The argument "max.dist" sets a maximum distance (geoR takes all distances 
by 
default)
the argument "uvec" allows you to specify a vector with the wanted 
distance classes
(similarly to breaks in histogram)

?variog has more detais otherwise let me know


Paulo Justiniano Ribeiro Jr
LEG (Laboratorio de Estatistica e Geoinformacao)
Universidade Federal do Parana
Caixa Postal 19.081
CEP 81.531-990
Curitiba, PR  -  Brasil
Tel: (+55) 41 3361 3573
VOIP: (+55) (41) (3361 3600) 1053 1066
Fax: (+55) 41 3361 3141
e-mail: paulojus AT  ufpr  br
http://www.leg.ufpr.br/~paulojus

On Sat, 28 Apr 2012, GEMA FERNANDEZ-AVILES CALDERON wrote:

> Dear Tom:
>
> I'm sorry if I have not formulate correctly the question.
>
> I am running this:
>
> #---------------------------------------------------
> library(geoR)
> x=read.table("Example.txt", header=TRUE)
> class(x)
>
> x<-as.geodata(obj=x,coords.col = 1:2, data.col = 3)
> plot(x)
> points(x,col=grey(seq(1,0,l=14)), main = "Regular Grid")
> cloud1 <- variog(x, option = "cloud")
> bin1 <- variog(x, option = "bin" , tolerance = 0)
>
> # graphic
>
> plot(cloud1, main = "classical estimator" )
> lines(bin1, type="p", lwd="4")
> plot(bin1, lwd=2, main = "Classical estimator", xlim=c(0,150))
> #---------------------------------------------------
>
> But, "bin1" has not contain 14 bins.
> How can specify it in geoR? Could you help me?
>
> Thanks,
> Gema
>
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> Gema Fern?ndez-Avil?s
>
> Department of Statistics
> Faculty of Law and Social Sciences
> University of Castilla-La Mancha at Toledo
>
> http://www.uclm.es/profesorado/gemafaviles/
>
>
>
> -----Mensaje original-----
> De: r-sig-geo-bounces at r-project.org en nombre de Tom Gottfried
> Enviado el: vie 27/04/2012 12:28
> Para: r-sig-geo at r-project.org
> Asunto: Re: [R-sig-Geo] geoR -- bins in experimental semivariogram
>
> Please express in R what you have done
> (see http://www.r-project.org/posting-guide.html)
>
> Am 27.04.2012 12:13, schrieb GEMA FERNANDEZ-AVILES CALDERON:
>>
>> Dear list:
>>
>> I have a 5x5 regular grid 100x100. When constructing the experimental semivariogram using gerR() I expected to have 14 different distances.
>> However, I obtained 10 semivariogram points corresponding to 10 bins.
>>
>> - Which is exactly a bin?
>
> the lag class (an interval on the real line of distances over which the
> semivariances are averaged).
>
>> - Which is the bin correspondence wiht the 14 initial distances.
>
> that depends on what you refer to with "14 initial distances".
>
>> - Why don't the first bin is not exactly 25?
>
> I suspect because you did not specify it that way (i.e. first lag class
> corresponding to [0,25)).
>
> Tom
>
>> - The dataset is the following.
>>
>> Thanks in advance,
>> Gema
>>
>> #########################################3
>> x	y	dat
>> 0	0	19.64253569
>> 25	0	20.67413804
>> 50	0	11.39907369
>> 75	0	8.721311665
>> 100	0	14.19476285
>> 0	25	9.755908087
>> 25	25	18.9788189
>> 50	25	14.05059221
>> 75	25	11.76423327
>> 100	25	10.42562093
>> 0	50	6.559737009
>> 25	50	4.882232635
>> 50	50	10.7619423
>> 75	50	9.096456345
>> 100	50	10.6894209
>> 0	75	14.87976528
>> 25	75	5.372505287
>> 50	75	5.712214162
>> 75	75	4.431458459
>> 100	75	15.69477576
>> 0	100	12.77014999
>> 25	100	1.366809445
>> 50	100	4.359141225
>> 75	100	6.607783644
>> 100	100	10.25674201
>>
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>>
>> Gema Fern?ndez-Avil?s
>>
>> Department of Statistics
>> Faculty of Law and Social Sciences
>> University of Castilla-La Mancha at Toledo
>>
>> http://www.uclm.es/profesorado/gemafaviles/
>>
>> 	[[alternative HTML version deleted]]
>>
>>
>>
>>
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>
> -- 
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> 85350 Freising / Germany
> Phone: ++49 (0)8161 715324
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>
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