similar to: UPGMA

I haven't been an R lister for a bit, but I hope to enlist someone's help here. I think this is a simple question, so I hope the answer is not much trouble. Can you please respond directly to this email address in addition to the list (if responding to the list is warranted)? I have a histogram and I want to see if the data fit a Poisson distribution. How do I do this? It is

Sorry to bother you kind folks again with my questions. I am trying to learn as much as I can about all this, and I will admit that I don't have the proper background, but I hope that someone can at least point me in the correct direction. I have created a test matrix for what I want to do: s1 s2 s3 s4 s5 s1 10 5 0 8 7 s2 5 10 0 0 5 s3 0 0 10 0 0 s4 8 0 0 10 0 s5 7

I have a matrix of similarity scores that I want to convert into a matrix of dissimilarity scores so that I can apply some clustering methods to the data. That is, high values in my matrix signify similarity and low values (zero being the lowest) signify no similarity. What functions/options in R or its packages are available for making this kind of transformation of a matrix?

Hi, I am clustering objects using the agnes() function and the UPGMA clustering method (function = "average"). Everything works well, but apparently something is wrong with the dendrogram. For example: x<-c(102,102.1,112.5,113,100.3,108.2,101.1,104,105.5,106.3) y<-c(110,111,110.2,112.1,119.5,122.1,102,112,112.5,115) xy<-cbind(x,y) library(cluster) UPGMA.orig<-agnes(x)

Hola a tod en s, Soy nuevo en R-help-es, por lo que perdonadme si debería haber mandado este email a una sección en particular. Quería consultaros un error que me aparece en R al hacer una matriz de disimilitud a partir de una tabla con 6000 columnas x 11000 filas. El mensaje que da R es "cannot allocate vector of size 10Gb", y me resulta extraño ya que tengo 64 Gb de RAM disponible.

Hi all, Has anyone got a function to perform clustering by Flexible UPGMA (Un-weighted Pair Group Using Arithmetic Averaging) . It does not seem to exist in any R package. Regards, Ton -- Laboratoire d'Hydro?cologie Quantitative 3 bis, Quai Chauveau - CP 220 69336 LYON cedex 09 t?l. : +33 (0)4.72.20.89 20 fax : +33 (0)4.78.47.78.75 mail : ton.snelder at cemagref.fr

Hola Rubén, Totalmente de acuerdo con los consejos de Carlos. Ten en cuenta que aunque R disponga de varios (bastantes) GB de memoria, algunos de los objetos que va creando durante el proceso pueden consumirla por completo. Es decir, que aunque tu ordenador tenga 64GB de RAM, es posible que no queden 10 GB libres para almacenar un objeto (porque ya hay demasiados objetos grandes en la

Antes de nada, me gustaría daros las gracias por toda vuestra ayuda. He estado probando todo lo que me habéis dicho a la vez, y no hay manera, sigo teniendo el problema con el espacio. En cuanto al tamaño de la base de datos, es más grande de lo que puse, me equivoqué y puse el tamaño de una base anterior con la que estuve trabajando, la actual tiene 36866 filas x 6500 columnas. He seguido todas

Yo creo que el problema principal está en betapart.core(), que crea y mantiene simultáneamente en memoria varios objetos de alrededor de 1 Gb que luego combina en una lista... Probablemente es entre las líneas el código de betaper.core donde hay que ir eliminando objetos. Saludos, Marcelino El 22/12/2015 a las 18:26, Carlos J. Gil Bellosta escribió: > Hola, ¿qué tal? > > Yo no

Hello, I am relatively new to R and I am working through the code that is provided in the book Numerical Ecology with R and I have run across an error message that I can't seem to figure out. I am using the vegan, ade4, gclus and cluster packages. The code is as follows: # Ordered community table # Species are ordered by their weighted averages on site scores or <- vegemite(spe,

Hello, I would like to know if there is a function in R that will test for normality and handle censored data sets. Currently, I evaluate each censored data set by the extent to which a normal scores plot approximate a straight line. For complete data sets I use shapiro.test(). Below is an example of a censored data set. data1<-c(0.00, 0.00, 0.00, 5.86, 5.17, 8.17, 5.12, 4.92, 7.08,

I yum updated yesterday and it updated chrome from 44.x to 45.x. It runs but it has errors going to web pages and won't load its own settings/extension pages either. I ran chrome from the command-line and see these errors: $ google-chrome libGL error: dlopen /usr/lib/dri/swrast_dri.so failed (/usr/lib/dri/swrast_dri.so: cannot open shared object file: No such file or directory) libGL error:

Hello, My name is Sivan and I am a master degree student in statistics,my problem is as follows: I have a dataset containing gene sequences and I would like to create a phylogenetic tree from it. The problem that I can't seem to find a function to do this kind of operation. I read the ape package manual and I haven't found a command that takes raw data and turns it into a tree. does anyone

Hello, I am attempting to assign significance levels to a UPGMA cluster analysis as part my doctoral research. The pvclust function works well but doesn't include the similarity index I need (morisita's) as an option for computing a distance matrix. Morisita's is available in vegdist in the VEGAN library but I am having a hard time getting the vegdist function to "direct

I am beginning to work with the 'ape' package in R, and have run into some trouble. I generated a UPGMA tree based on DNA sequence distance in Paup* and read it into R, where it became an object of class "phylo". However, I need it to be classified as a "dendrogram" for my purposes (to use it to order the layout of a heatmap). I get an error using as.hclust.phylo

(Seems to me that Icecast folks would be particularly concerned about this. Please consider the following, lend your signatures, and also *send it on* to appropriate interested parties. If you are a blogger or know clueful bloggers, please try to have it posted in a highly visible forum. -- Seth Johnson) Hello folks, Please review the important joint statement below, related to the WIPO

Hi, this is rather a (presumed) bug report than a question because I can solve my personal statistical problem by working with hclust instead of agnes. I have done a complete linkage clustering on a dist object dm with 30 objects with agnes (R 1.8.0 on RedHat) and I want to obtain the partition that results from a cut at height=0.4. I run > cl1a <- agnes(dm, method="complete")

Hi, this is rather a (presumed) bug report than a question because I can solve my personal statistical problem by working with hclust instead of agnes. I have done a complete linkage clustering on a dist object dm with 30 objects with agnes (R 1.8.0 on RedHat) and I want to obtain the partition that results from a cut at height=0.4. I run > cl1a <- agnes(dm, method="complete")

Hello, In the documentation for agnes in the package 'cluster', it says that NAs are allowed, and sure enough it works for a small example like : > m <- matrix(c( 1, 1, 1, 2, 1, NA, 1, 1, 1, 2, 2, 2), nrow = 3, byrow = TRUE) > agnes(m) Call: agnes(x = m) Agglomerative coefficient: 0.1614168 Order of objects: [1] 1 2 3 Height (summary): Min. 1st Qu. Median Mean 3rd

Dear R users, I discovered something strange using the function agnes() of the cluster package on R 3.0.1 and on R 2.14.1. Indeed, the clusterings obtained are different whereas I ran exactly the same code. I quickly looked at the source code of the function and I discovered that there was an important change: agnes() in R 2.14.1 used a FORTRAN code whereas agnes() in R 3.0.1 uses a C code.