similar to: restructuring matrix

Let's say i have a = c(1, 4, 5) b = c(2, 6, 7) and i have matrix m, what's an efficient way of access m[1, 2], m[4, 6], m[5, 7] like of course m[a, b] = is not going to do, but what's an expression that will allow me to have that list? Thanks! -- View this message in context: http://www.nabble.com/Simplest-question-ever...-tf3329894.html#a9258932 Sent from the R help mailing list

Hi all, I have this list of strings [1] "1 ,2 ,3" "4 ,5 ,6" Is there an efficient way to convert it to data.frame: V1 V2 V3 1 1 2 3 2 4 5 6 Like I can use strsplit to get to a list of split strings.. and then use say a = strsplit(mylist, ",") data.frame(V1 = lapply(a, function(x){x[1]}), V2 = lapply(a, function(x){x[2]}),.....) but i'm

Dear All, I am attempting to use the FANNY fuzzy clustering function in R (Kaufman & Rousseeuw, 1990), found in the "cluster" package. I have run into a variety of difficulties; the two most crucial difficulties are enumerated below. 1. Where is the 'm' parameter in FANNY? In _Finding Groups in Data: An Introduction to Cluster Analysis_ (1990) by Kaufman & Rousseeuw,

Full_Name: Guan-Hua Huang Version: 2.0.1 OS: Linux Submission from: (NULL) (140.113.114.123) I install the package cluster by using install.packages("cluster"). After install it, it runs fine for function clara, but it does not work for function fanny. I did the following things: library(cluster) set.seed(21) x <- rbind(cbind(rnorm(10, 0, 0.5), rnorm(10, 0, 0.5)),

Dear All, My R version: 2.0.1 ; OS using: Linux. I install the package cluster by using install.packages("cluster"). After install it, it runs fine for function clara, but it does not work for function fanny. I did the following things: library(cluster) set.seed(21) x <- rbind(cbind(rnorm(10, 0, 0.5), rnorm(10, 0, 0.5)),cbind(rnorm(15, 5, 0.5), rnorm(15, 5, 0.5)),cbind(rnorm(

Hello, Instead of receiving only one message when somebody send a question or a answer, I receive 2 messages with exactly the same contents inside. Is it the same for you? Thank you, Fanny -------------------------- Fanny AZIZA École Nationale Vétérinaire d'Alfort Mail: faziza@vet-alfort.fr Tél. 01 43 96 70 33 [[alternate HTML version deleted]]

Hello List, My question is an elementary one. I have run a fuzzy kmeans cluster using FANNY to group freshwater fish assemblages. I then went in the field to validate that classification and have retrieved new assemblage data for a new suite of streams. Therefore I would like to use Predict to determine how well the original clustering fits the new data. However I have not figured out a

Greetings, I am reasonably experienced with R but I recently tried to do some clustering using the "cluster" package, in order to see if it would help. I only tried this once with the 1.3.1 version and it worked (I don't quite remember which method I used). Now, I tried with the 1.4.0 version and no clustering function seems to work with matrices that contain NAs, even though

Hello, I would like to use my own dissimilarity matrix in a PAM clustering with method "pam" (cluster package) instead of a dissimilarity matrix created by daisy. I read data from a file containing the dissimilarity values using "read.csv". This creates a matrix (alternatively: an array or vector) which is not accepted by "pam": A call

Hi, I am using fanny and I have estrange results. I am wondering if someone out there can help me understand why this happens. First of all in most of my tries, it gives me a result in which each object has equal membership in all clusters. I have read that that means "the clustering is entirely fuzzy". Looking at the graphics it is really difficult to understand how objects with so

Regarding Tengfei Yin's post about an error trying to install "cluster" in 2.13.0, I have gotten an error with this package when trying to install the released version of 2.12.0. Here is the output on an Ubuntu Linux system: begin installing recommended package cluster * installing *source* package 'cluster' ... ** libs make[3]: Entering directory

Hello, I want to make a fuzzy classification from a dissimilarity matrix (calculated with daisy from package 'cluster'). I have tried to use fanny (package cluster) but I have the same problems than described in a previous message (http://tolstoy.newcastle.edu.au/R/help/05/05/4546.html) i.e. it always gives me two clusters in the results (even if k is different from 2) with the same

Hi All, For the function "bclust"(e1071), the argument "base.method" is explained as "must be the name of a partitioning cluster function returning a list with the same components as the return value of 'kmeans'. In my understanding, there are three partitioning cluster functions in R, which are "clara, pam, fanny". Then I check each of them to

Dear all, I'm trying to obtain a fuzzy clustering with fanny from the cluster package, using a given set of data. That worked just fine. I have another separate sample of data from the same problem. For each case in this new sample I would like to know their membership coefficients with respect to the clustering obtained with the first dataset. In effect I want to have a kind of prediction

Dear R-help list members i would like to use R to produce clustering or partitioning of a dataset. I am trying to use the functions: - hierclust() of the package multiv -pam(), agnes() and fanny() of the package cluster But I cannot get any result because of lack of memory. Would you know any clustering function not to greedy in memory? I have tried to expand my memory limit with memory.limit()

Hello, i use i.e. the cluster-package and the fanny-object to construct some cluster's and get the membership'S for every "Person" & Cluster ! My finally problem is to match efficient the data and the results's togehter in one table! Until now i use the ODBC-Package and save both in a access-file and copy them together, but i can't be sure that the sorting is the

Hi, I'm trying to use a similarity matrix (triangular) as input for pam() or fanny() clustering algorithms. The problem is that this algorithms can only accept a dissimilarity matrix, normally generated by daisy(). However, daisy only accept 'data matrix or dataframe. Dissimilarities will be computed between the rows of x'. Is there any way to say to that your data are already a

I have "small" problem ... with the cluster library each time I try to use the "agnes","pam","fanny" functions with more than 20000 elements I get the following error: >Error in vector("double", length) : negative length vectors are not allowed >In addition: Warning message: >NAs introduced by coercion But with the clara

Dear all, I have a problem when using some classification functions (Kmeans, PAM, FANNY...) with a distance matrix, and i would to understand how it proceeds for the positioning of centroids after one execution step. In fact, in the classical formulation of the algorithm, after each step, to re-position the center, it calculates the distance between any elements of the old cluster and its

https://bugs.freedesktop.org/show_bug.cgi?id=70388 Priority: medium Bug ID: 70388 Assignee: nouveau at lists.freedesktop.org Summary: [NV34] failed to idle channel 0xcccc0000 Severity: critical Classification: Unclassified OS: Linux (All) Reporter: rosti.bsd at gmail.com Hardware: x86 (IA32)