CODEWITHSUNDEEP
rfunction
Pascal
Pascal

Reputation: 1672

R variable not found, but specifically defined

I have written a function to run phylogenetic generalized least squares, and everything looks like it should work fine, but for some reason, a specific variable which is defined in the script (W) keeps coming up as undefined. I have stared at this code for hours and cannot figure out where the problem is.

Any ideas?

myou <- function(alpha, datax, datay, tree){
    data.frame(datax[tree$tip.label,],datay[tree$tip.label,],row.names=tree$tip.label)->dat
    colnames(dat)<-c("Trait1","Trait2")
    W<-diag(vcv.phylo(tree)) # Weights
    fm <- gls(Trait1 ~ Trait2, data=dat, correlation = corMartins(alpha, tree, fixed = TRUE),weights = ~ W,method = "REML")
    return(as.numeric(fm$logLik))
}

corMartins2<-function(datax, datay, tree){
    data.frame(datax[tree$tip.label,],datay[tree$tip.label,],row.names=tree$tip.label)->dat
    colnames(dat)<-c("Trait1","Trait2")
    result <- optimize(f = myou, interval = c(0, 4), datax=datax,datay=datay, tree = tree, maximum = TRUE)
    W<-diag(vcv.phylo(tree)) # Weights
    fm <- gls(Trait1 ~ Trait2, data = dat, correlation = corMartins(result$maximum, tree, fixed =T),weights = ~ W,method = "REML")
    list(fm, result$maximum)}




#test


require(nlme)
require(phytools)
simtree<-rcoal(50)
as.data.frame(fastBM(simtree))->dat1
as.data.frame(fastBM(simtree))->dat2

corMartins2(dat1,dat2,tree=simtree)

returns "Error in eval(expr, envir, enclos) : object 'W' not found"

even though W is specifically defined!

Thanks!

Upvotes: 2

Views: 2513

Answers (2)

jthetzel
jthetzel

Reputation: 3623

The example is not reproducible for me, as lowerB and upperB are not defined, however, perhaps the following will work for you, cbinding dat with W:

myou <- function(alpha, datax, datay, tree){
    data.frame(datax[tree$tip.label,],datay[tree$tip.label,],row.names=tree$tip.label)->dat
    colnames(dat)<-c("Trait1","Trait2")
    W<-diag(vcv.phylo(tree)) # Weights
            ### cbind W to dat
            dat <- cbind(dat, W = W)
    fm <- gls(Trait1 ~ Trait2, data=dat, correlation = corMartins(alpha, tree, fixed = TRUE),weights = ~ W,method = "REML")
    return(as.numeric(fm$logLik))
}

corMartins2<-function(datax, datay, tree){
    data.frame(datax[tree$tip.label,],datay[tree$tip.label,],row.names=tree$tip.label)->dat
    colnames(dat)<-c("Trait1","Trait2")
    result <- optimize(f = myou, interval = c(lowerB, upperB), datax=datax,datay=datay, tree = tree, maximum = TRUE)
    W<-diag(vcv.phylo(tree)) # Weights
    ### cbind W to dat
    dat <- cbind(dat, W = W)
    fm <- gls(Trait1 ~ Trait2, data = dat, correlation = corMartins(result$maximum, tree, fixed =T),weights = ~ W,method = "REML")
    list(fm, result$maximum)}




#test
require(phytools)
simtree<-rcoal(50)
as.data.frame(fastBM(simtree))->dat1
as.data.frame(fastBM(simtree))->dat2

corMartins2(dat1,dat2,tree=simtree)

Upvotes: 5

mathematical.coffee
mathematical.coffee

Reputation: 56905

The error's occuring in the gls calls in myou and corMatrins2: you have to pass in W as a column in dat because gls is looking for it there (when you put weights = ~W as a formula like that it looks for dat$W and can't find it).

Just change data=dat to data=cbind(dat,W=W) in both functions.

Upvotes: 6

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