search for: cooccur

...ing standardized data) >all2 Year standard 1 2001 0.034246575 2 2001 0.000000000 ... 141 2008 0.012820513 142 2008 0.230769231 I have plotted separate histograms for each year using hist(all2[Year==2001,]$standard,breaks=seq(0,.7,.005),ylim=c(0,10),main="2001",xlab="cooccured/total sites",ylab="frequency of cooccurance") hist(all2[Year==2002,]$standard, ... hist(all2[Year==2003,]$standard, ... etc. I would like to clean it up a bit by plotting the data using xyplot from library(lattice) of the standardized.data. My questions are: a. Is there a functi...

Hey all, I feel like the solution to this problem should be relatively simple, but for some reason I can't find answers or come up with my own solution. Given the dataframe: (SpA and SpB not important, want to look at distribution of cooccurance for each year) Year SpA SpB Coocc 2000 0 2000 2 2000 1 2001 8 2001 2 2001 0 2001 0 2002 1 2002 2 How can I apply different functions to the Coocc of each year? (Note: Different lengths for each year, ie, length(Year==2000)!=length(Year==2001)) For example, if Year==2000, function(x)...

...each variable. Read some papers concerning smallest space analysis, but it does not seems implemented in any R package (and my protamming skills are =0). Non metric MDS gives error messages, probably because of the dichotomous character of my variables. My aim is basically to obtain a 2D plot with cooccurence expressed as distance between plots (variables). Any advice to such issue? Thanks in advance and sorry for this long post marco -- View this message in context: http://r.789695.n4.nabble.com/Dichotomous-variables-tp3721550p3721550.html Sent from the R help mailing list archive at Nabble.com.

...he best algorithm to use is k-means although I'm not sure about that -- I would have preferred a k dimensional space with a binary cluster in each dimension so a word can belong to 0..k clusters, but I digress... I can measure the strength of correlation between words fairly easily by counting cooccurance divided by frequency of each word, giving a euclidian distance, although this doesn't work especially well for rare words. However I don't have coordinates as such, and deriving them given distance is non-trivial. Now, as I understand k-means, it uses euclidian distance rather than c...

Hello All! I am trying to plot the frequency of species coocurrance. If given a data set similar like this...(V1="species A", V2="species B", V3="frequency of cooccurance") > data V1 V2 V3 1 A B 0 2 A C 2 3 A D 5 4 B C 0 5 B D 1 6 C D 0 > data1<-as.data.frame(lapply(data,function(x)(rep(x,data$V3)))) > as.data.frame(data1[-1]) > fdata<-ftable(as.data.frame(data1[-3])) > fdata V2 B C D V1 A 0 2 5 B 0 0 1 C...

...ll$ncp, quali = acm$call$quali, name.group = afm$call$name.group, sim = sim) group_afm = list(coord = afm$group$coord, cos2 = afm$group$cos2, contrib = afm$group$contrib) res = list(eig = acm$eig, var = acm$var, ind = acm$ind, group = group_afm, call = acm_call, cooccur = compte2, reord = catego_num2, cramer = res2) class(res) <- c("catego", "list ") return(res) } Regards Vijayan Padmanabhan "What is expressed without proof can be denied without proof" - Euclide. Can you avoid printing this? Think of the envi...