Dear Matthew

Thank you for the helpful recommendation for formatting the matrix. I will
work on determining sensitivity for replacing NAs. I know looking at
inverted matrices from phylogies the matrix is sparse (there are many "."
Instead of values) maybe I will try to incorporate these into the M1 matrix

Thanks again
Dean

On Thursday, June 5, 2014, Matthew Wolak <s06mw3@abdn.ac.uk> wrote:

> Dear Dean,
>
> MCMCglmm needs the generalized inverse (your M1) formatted in a specific
> way - for example as the "dgCMatrix" class defined in the Matrix package.
>
> Substituting the lines below gets the model to work.  NOTE, I had to
> substitute "0.00" wherever you had NA in the M matrix in order to invert
> it.  This is probably not the best practice and maybe some simulations
> to determine the sensitivity of your parameter estimates when there is
> error (i.e., saying NA=0.00) in your genetic distance matrix.
>
> INSTEAD OF:
>
> M1<-ginv(M) #I have also been using M in the model with the same error
>
> dimnames(M1) <- list(c("sp1","sp2","sp3","sp4"
> ),c("sp1","sp2","sp3","sp4"))
>
>
> DO
>
> M1 <- as(ginv(M), "dgCMatrix")
>
> M1@Dimnames <- list(c("sp1", "sp2", "sp3", "sp4"), c("sp1", "sp2", "sp3",
> "sp4"))
>
>
>
> Sincerely,
> Matthew
>
> ....................................................
> Dr. Matthew E. Wolak
> School of Biological Sciences
> Zoology Building
> University of Aberdeen
> Tillydrone Avenue
> Aberdeen AB24 2TZ
> office phone: +44 (0)1224 273255
>
> On 04/06/14 19:33, Dean Castillo wrote:
>
>> I am currently using MCMCglmm to model species ability to cross with one
>> another. For most of the datasets species relationships can be defined by
>> a
>> phylogeny and I can simply incorporate this information into the model
>> using the pedigree or ginverse options.
>>
>> I would like to run similar models now but for subspecies/races that do
>> not
>> have well defined phylogenies (the questions is identical). I have genetic
>> distances for some of the species in these data sets (some I have complete
>> pairwise genetic distances, others I only have distances for specific
>> species pairs). I have considered making a  simple NJ tree based on
>> distance matrices and incorporating this "phylogeny" via pedigree or
>> ginverse, but this strategy will not work without complete pairwise
>> distances.
>>
>> Is there a way to utilize the distance matrix (complete or more sparse)
>> directly? Since the genetic distance matrix looks very similar to the
>> relationship matrix "A" in the MCMCglmm tutorial and coursenotes I tried
>> incorporating it into the model but have run into a few errors.
>>
>> Here is the fake data I have been playing around with. Any help would be
>> greatly appreciated
>>
>> #Genetic Distance Matrix. I have also been replacing NA with 0 but still
>> encounter same error
>>
>> x <- c( 0.07 ,0.08, 0.11,NA,
>>
>>   0.16, NA)
>>
>> M <- matrix(0, 4, 4)
>>
>> M[lower.tri(M)] <- x
>>
>> M <- t(M)
>>
>> M[lower.tri(M)] <- x
>>
>> dimnames(M) <- list(c("sp1","sp2","sp3","sp4"
>> ),c("sp1","sp2","sp3","sp4"))
>>
>> diag(M)<-1
>>
>> #Fake response variable, species ID, and categorical predictor
>>
>>
>> y<-c(5,5,6,6,10,10,12,11,4,3,4,5,11,12,13,14)
>>
>> species<-c("sp1","sp1","sp1","sp1","sp2","sp2","sp2","sp2","
>> sp3","sp3","sp3"
>> ,"sp3","sp4","sp4","sp4","sp4")
>>
>> species<-as.factor(species)
>>
>> ms<-c(0,0,0,0,1,1,1,1,0,0,0,0,1,1,1,1)
>>
>> data<-data.frame(y,ms,species)
>>
>>
>> # want to run a model for y~ma taking into account species
>>
>> library(MCMCglmm)
>>
>> #define prior
>>
>> p.var<-var(y)
>>
>> prior1=list(R=list(V=p.var/2, n=1), G=list(G1=list(V=p.var/2, n=1)))
>>
>> library(MASS)
>>
>> M1<-ginv(M) #I have also been using M in the model with the same error
>>
>> dimnames(M1) <- list(c("sp1","sp2","sp3","sp4"
>> ),c("sp1","sp2","sp3","sp4"))
>>
>> model1<-MCMCglmm(y~ms,random=~species,ginverse=list(species=
>> M1),prior=prior1
>> ,data=data)
>>
>> #The error I receive.
>>
>> Error in FUN(X[[1L]], ...) :
>>
>>    trying to get slot "Dim" from an object of a basic class ("matrix")
>> with
>> no slots
>>
>>       [[alternative HTML version deleted]]
>>
>> _______________________________________________
>> R-sig-mixed-models@r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>>
>
>
>
> The University of Aberdeen is a charity registered in Scotland, No
> SC013683.
> Tha Oilthigh Obar Dheathain na charthannas clàraichte ann an Alba, Àir.
> SC013683.
>

	[[alternative HTML version deleted]]

