[R-sig-Geo] testing nlme models for spatial correlation

[Thierry Onkelinx]

Dear Javier,

Your problem is hard to understand without a reproducible example. You only
gives the code, not the data nor the error message.

Best regards,

ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 Anderlecht
Belgium

To call in the statistician after the experiment is done may be no more
than asking him to perform a post-mortem examination: he may be able to say
what the experiment died of. ~ Sir Ronald Aylmer Fisher
The plural of anecdote is not data. ~ Roger Brinner
The combination of some data and an aching desire for an answer does not
ensure that a reasonable answer can be extracted from a given body of data.
~ John Tukey

2017-08-01 16:36 GMT+02:00 Javier Moreira <javiermoreira at gmail.com>:

> Thanks Thierry,
> I would check that info.
> Any ideas why if i choose the finest level of random effects as
> /SUBMUESTREO and run model 4 (with correlation) wont let me?
> If i undesrtand you wel, you adress more the second question i made, im
> all right?
> Thanks!
>
>
> El 1 ago. 2017 8:10 a. m., "Thierry Onkelinx" <thierry.onkelinx at inbo.be>
> escribió:
>
> Dear Javier,
>
> The correlation structure in nlme only works on the residuals within the
> finest level of random effect. Observations in different random effect are
> independent.
>
> Have a look at the INLA package (http://www.r-inla.org). INLA allows for
> correlated random effects. So you have spatial correlation among the random
> effects (instead of among residuals). INLA has options for correlations
> along a 2D regular grid, a neighbourhood graph or a mesh. If you want an
> book on this, I recommend Zuur et al (2017) Beginner's Guide to Spatial,
> Temporal and Spatial-Temporal Ecological Data Analysis with R-INLA.
>
> Best regards,
>
>
> ir. Thierry Onkelinx
> Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
> Forest
> team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
> Kliniekstraat 25
> 1070 Anderlecht
> Belgium
>
> To call in the statistician after the experiment is done may be no more
> than asking him to perform a post-mortem examination: he may be able to say
> what the experiment died of. ~ Sir Ronald Aylmer Fisher
> The plural of anecdote is not data. ~ Roger Brinner
> The combination of some data and an aching desire for an answer does not
> ensure that a reasonable answer can be extracted from a given body of data.
> ~ John Tukey
>
> 2017-08-01 11:31 GMT+02:00 Javier Moreira <javiermoreira at gmail.com>:
>
>> hi,
>> im trying to generate different models to account for spatial correlation.
>> Im using nlme package, and mixed models, in order to compare two models,
>> one that doesnt include the spatial correlation and one that does.
>>
>> Its a nested design, one that has 4 leves,
>> BLOQUE/ AMBIENTE/ TRATAMIENTO/ SUBMUESTREO
>> Its a harvest set data, with multiple point of data/ treatment, so the
>> last
>> level account for another term in the error for "sub-muestreo".
>>
>> My first problem its, when i try to add de correlation term to the model,
>> i
>> cant, when the random effects are taken to the level /SUBMUESTREO, and i
>> have to leave it to the level of TRATAMIENTO.
>> When i do that, i have 2 differences between models, the term accounting
>> for sub-muestreo, and the spatial correlation.
>>
>> #MODELO 2##
>> attach(base_modelo3)
>> str(base_modelo3)
>> data1=base_modelo3
>> str(data1)
>> data1=groupedData(REND.~1|BLOQUE/AMBIENTE/TRATAMIENTO/SUBMUESTREO,
>> data=data1, units=list(y="(ton/ha)"))
>> data1$TRATAMIENTO =factor(data1$TRATAMIENTO)
>> data1$BLOQUE =factor(data1$BLOQUE)
>> data1$AMBIENTE =factor(data1$AMBIENTE)
>>
>> modelo2_MM<-lme(REND.~1+TRATAMIENTO*AMBIENTE,
>>                 random=~1|BLOQUE/AMBIENTE/TRATAMIENTO/SUBMUESTREO,
>>                 weights=varComb(varIdent(form=~1|TRATAMIENTO)),
>>                 data=data1,
>>                 control=lmeControl(niterEM=150,msMaxIter=200))
>> summary(modelo2_MM)
>> anova(modelo2_MM)
>>
>> ##MODELO 4##
>>
>> modelo4_MM<-lme(REND.~1+TRATAMIENTO*AMBIENTE,
>>                 random=~1|BLOQUE/AMBIENTE/TRATAMIENTO,
>>                 weights=varComb(varIdent(form=~1|TRATAMIENTO)),
>>                 correlation=corExp(form=~X+Y,nugget=T),
>>                 data=data1,
>>                 control=lmeControl(niterEM=150,msMaxIter=200))
>> summary(modelo4_MM)
>> anova(modelo4_MM)
>>
>> My second problem is, that i need to get the specific parameter for the
>> error term that belongs to the spatial correlation, in order to map it.
>> For
>> what i watch, what lme does is send it to the general error, and so, what
>> i
>> could do is make the differences between the residuals of these two
>> models.
>> so, its essetial to get the exact same model, except for the correlation
>> structure.
>> If anybody knows how to get the specific term of error accounting for the
>> correlation, it would be wonderful.
>>
>> E24=residuals(modelo24_3,type = "response")
>> E40=residuals(modelo4_MM,type = "response")
>> EE=E24-E40
>> post=data.frame(E24,E40,EE,data1$X,data1$Y)
>>
>> coordinates(post)<-c("data1.X","data1.Y")
>> coor_post<-coordinates(post)
>>
>> bubble(post,"E24",main="residuos modelo 2")
>> bubble(post,"E40",main="residuos modelo 4")
>> bubble(post,"EE",main="Est.espacial removida por Modelo 4")
>>
>> thanks!
>>
>> --
>> Javier Moreira de Souza
>> Ingeniero Agrónomo
>> 099 406 006
>>
>>         [[alternative HTML version deleted]]
>>
>> _______________________________________________
>> R-sig-Geo mailing list
>> R-sig-Geo at r-project.org
>> https://stat.ethz.ch/mailman/listinfo/r-sig-geo
>
>
>
>

	[[alternative HTML version deleted]]