I am currently testing species co-occurrence patterns using null models and
the oecosimu() function within the vegan() package. My issue is that none of
the methods appear to be the ones that I want. The methods listed are r0,
r1, r2, r2dtable, swap, tswap. However, I want to know how to go about
i
Another way would be a which statement.
good_dataset=data[,which(colSums(data)!=0)]
I believe this depends on how the data are structured though.
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m> wrote:
> Dallas drakeresearchlab.com> writes:
>
> > I am currently testing species co-occurrence patterns using null models
> and
> > the oecosimu() function within the vegan() package. My issue is that
> none of
> > the methods appear to be the ones that I w
Fantastic! I'll avoid the sequential models and will look into the r0 and
r1 methods. Thank you.
Tad
On Wed, Jan 25, 2012 at 3:03 AM, Jari Oksanen [via R] <
ml-node+s789695n4326620...@n4.nabble.com> wrote:
> Dallas drakeresearchlab.com> writes:
>
> >
> > I
I think this is what you are getting at. Hope this helps.
#index data to determine what low and high levels of tvHrs are (I said
anything over 15 hours is considered 'high')
index=which(tvHrs > 15)
#Plot the first plot, which is the 'high', only using values from crimeDvp
that are in 'index' (c
The as.matrix (and as.table or as. vector or as.numeric ...) command takes
the object that you wish to convert as an argument. So the code below will
actually perform the conversion from table to matrix.
> newmatrix<- as.matrix(matrix_v3)
A way to see what form your data are taking is to use the
I believe this is what you want to do, though it may need tweaking.
#Make up some data
> a=seq(1,100,by=1)
> b=runif(100,0,0.5)
#Make a matrix
> matrix=cbind(a,b)
#Subset the matrix based upon values of interest
> subsetmatrix=matrix[which(b<0.1),]
#Plot values
>
> plot(subsetmatrix[,2]~subset
Okay. I think I understand now. You would just like nothing to be plotted for
the points below a certain threshold but there will still be that space
indexing where the point would've gone. I hope I have this right.
So what you could do to fix that is to make a new matrix (still including
all the
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