similar to: 50993 point distance matrix, too big to as.matrix, looking for another way to calculate point-level summary

Hi, I am trying to combine a long list but I can't work out how to do it, for example: abun<-list(rep(0,5),rep(0,7),rep(0,4),rep(0,10)) nb<-c(5,5,1,8) fill.abun <- function(x, y) { set <- sample(1:length(x), size = y) x[set] <- rlnorm(length(set)) return(x) } abun <- mapply(fill.abun, abun, nb) abun ## I want all the data in one

Hi All, I am writing a simulation that examines the effects of species extinctions on ecological communties by sequentially removing individuals of a given species (sometimes using weighted probabilities) and replacing the lost individuals with species identities randomly sampled from the remaining individuals. Thus I use two dataframes. One contains all the individuals and their species

Hello, I am really new to R and it's still a challenge to me. Currently I'm working on my Master's Thesis. My supervisor works with SAS and is not familiar with R at all. I want to run an Anova, a tukey-test and as a result I want to have the tukey-grouping ( something like A - AB - B) I came across the HSD.test in the agricolae-package, but... unfortunately I do not get an output

I have to solve a clustering problem. My first step is to determinate the number of clusters, that's why I 'm using the Calinski index ( [tr(b)/(k-1)]/[tr(w)/(k-1)] ) which i try to maximize to have the best number of clusters. A function is already implemented in R to calculate this index : clustIndex(cl,x, index="calinski") where cl is the result of a clustering method ,

Hello, here is my problem, After looking at the mail archives, I found a description of the error I get when I use this package. At first I even tought that they were showing how to solve it. But the thing is that by saying "the programmer forgot drop=FALSE" doesn't show me how I should get rid of the problem I have looked inside the package very quickly and I found three

Greetings, I am new to R and am hoping to get some tips from experienced R-programmers. I have a dataset that I've read into R as a dataframe. There are 5 columns: Plot location,species name, a species number code (unique to each species name), abundance, and treatment. There are 272 plots in each treatment, but only the plots in which the species was recorded have an abundance value. For

Hi, I was wondering what the best equivalent to SAS's FASTCLUS and PROC CLUSTER would be. I need to be able to test the significance of the clusters by comparing the probability of obtaining an equal or greater pseudo F to the Bonferroni-corrected level. I will also need to plot r squared against the number of clusters. Thanks so much, Taisa [[alternative HTML version deleted]]

Hello all, I am using the clustering functions in R in order to work with large masses of binary time series data, however the clustering functions do not seem able to fit this size of practical problem. Library 'hclust' is good (though it may be sub par for this size of problem, thus doubly poor for this application) in that I do not want to make assumptions about the number of

Dear members of the list, I'm fitting ordinal regressions using polr, and in some models I get the error copied below. Dependent variable is an ordered factor of bird abundance categories, and predictors are continuous habitat variables. > ro6 <- polr(formula = abun ~ InOmbrot + Oliva.OC + ToCultAr + DivCulArb + AltitMax + COORXY) > summary(ro6) Re-fitting to get Hessian

Can anyone point me in the right direction of figuring out what downweight() is doing? I am using vegan to perform CCA on diatom assemblage data. I have a lot of rare species, so I want to reduce the influence of rare species in my CCA. I have read that some authors reduce rare species by only including species with an abundance of at least 1% in at least one sample (other authors use 5% as a

Dear all, below you find enclosed my message from January 9th and my program (attention: beginner). Thanks for both answers! a. However, as far as I know the cosine is not the same as the Pearson correlation (only in special cases). b. Reid Huntsinger's hint was very useful, however I had to transpose the matrix first, for I want to calculate the distance of the _rows_. Regards, Petra

Hi all. Although I am not subscribedto the list, I read it in regular basis. I moved from mp3 to Vorbis to encode all my music collection. Now I started wondering, as reading a mail from Erik Stenborg that Vorbis quality might not yet be ready for "production", since it is in beta. I find it _very_ high-quality, but I just wanted to ask about it to you, developers. I am using beta4

Is this a bug? do i have to complete a bug report? Is any other info needed? [root@nostromo ogg123]$ ./ogg123 -v -d oss /mnt/hdd/mp3/ripped/REM-Revival/track.08.ogg Playing from file /mnt/hdd/mp3/ripped/REM-Revival/track.08.ogg. Device: OSS audio driver output Author: Aaron Holtzman <aholtzma@ess.engr.uvic.ca> Comments: Outputs audio to the Open Sound System driver. Bitstream is 2

Hi, I would like to see a way to force R to be in interactive mode with a flag. So that the default behavior of being in interactive mode if the input is from a keybord can be overridden. Something like: R --interactive R --no-interactive octave has a flag like this and it words nicely for what I need (input from named pipe). Anyway, the fix is just a simple change to src/unix/system.c I can

Hi, I am new to clustering and was wondering why pvclust using "maximum" as distance measure nearly always results in p-values above 95%. I wrote an example programme which demonstrates this effect. I uploaded a PDF showing the results Here is the code which produces the PDF file: ------------------------------------------------------------------------------------- s <-

Hi, I have similarity value between string pairs in a mysql database. I need to construct the distance matrix which hclust can take and cluster the strings. Most of the examples I came across show how to construct the distance matrix using dist function. How can I code to construct distance matrix using the data in mysql db. Thanks a lot for any help. [[alternative HTML version deleted]]

Dear All: I am a newbie to R and as such i am posting this request for help. I am trying to use R to compute the "Calinski Harabasz (CH) Index ". The CH Index is available in the library SAGx. The version of R i am running is 2.2.1. I have my data in a CSV format which i read into R using the read.table() command. After the data has been read i am loading in the "SAGx"

Dear R Users: I am new to R and I am trying to do a cluster analysis on a single continuous variable using the Agnes [Agglomerative Nesting (Hierarchical Clustering) ] in the Package ‘cluster’. I was able to apply this clustering method to my data: ward1 <- Agnes(balances, diss= FALSE, metric = "euclidean", stand = TRUE, method = "ward", keep.diss =TRUE, keep.data =

Dear All, I would like to use the simprof function (clustsig package) but the available distances do not include Jaccard distance, which is the most appropriate for pres/abs community data. Here is the core of the function: > simprof function (data, num.expected = 1000, num.simulated = 999, method.cluster = "average", method.distance = "euclidean", method.transform =

Hi everyone, I am working with the dbFD function of the FD package, and there's something funny happening with the value of sing.sp in the output. Basically, I have a species-function matrix and a community matrix. One site in particular has 6 species, 4 of which have identical functional coding. I thus expect nbsp = 6 and sing.sp = 2 for this site. However, nbsp = sing.sp = 6. This