Re: [R] help filtering points from a scatterplot

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

Re: [R] help filtering points from a scatterplot

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

Re: [R] Problems with Cosine Similarity using library(lsa)

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

Re: [R] Multiple line-plot

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

Re: [R] Null models of species co-occurrence

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

Re: [R] Null models of species co-occurrence

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

Re: [R] drop columns whose rows are all 0

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. -- View this message in context: http://r.789695.n4.nabble.com/drop-columns-whose-rows-are-all-0-tp4324231p4325474.html Sent from the R help maili

[R] Null models of species co-occurrence

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