similar to: cluster analysis :: urgent

hi, I have my data time expressed in character string exple "5:20" (hour:min) and i want to convert these in times recognized by R. I have tried the POSIXct function: balise07$Hour <- as.POSXIct(balise07$Hour) but it didn't work. Do you know why? Do you know how i can convert my string character in a real time? Thanks Karine HEERAH Master 2 mention

hello, I have a problem to open an hdf file. i have downloaded the package 'hdf5' as it was advised on R seek. But when i try to load the file, the R console sends me an eror message: setwd("C:/Documents and Settings/Karine/Bureau/data/") #install.packages('hdf5') library("hdf5") sea_ice <- hdf5load("asi-s6250-20090704-v5i.hdf", load =

Hi everybody. i have 2 datasets : one with a long grid a lat grid and a bathymetry grid the second one only has the long and lat coordinates. So i want to know the bathymetry associated to the second dataset. I thought it was a good idea to do an interpolation between the two datasets. I find a script doing that on matlab but i want to do it on R. Do you how to do it? for ii =

Hi everybody, I have a longitude vector and a latitude one. Associated to these coordinates, i have a matrix with some data at some coordinates but not all. Lon <- seq(136.025,144.975,0.05) Lat <- rev(seq(-66.975,-65.525,0.05)) dim(z) <- c(Lon,Lat) And i have tried to apply to these data a kriging function. But first i need to reshape these 3 variables to have a dataframe

hi everybody, How can you plot some dates? I mean how can i have the tickmarks with the label of each date on my x axis? The dates i use are in POSIXct format, i don't know if it matters. thanks a lot Karine _________________________________________________________________ Consultez vos emails Orange, Gmail, Yahoo!, Free ... directement depuis HOTMAIL !

Hi All, A question from a newbie using R 2-5-0 on windows XP. Why is it that kmeans clustering with apparently the exact same parameters behaves so differently between the two following examples : > cl1 <- kmeans(subset(pointsUXO15555, select = c(2:4)), 10) Takes about 2 seconds to deliver a result > cl1 <- clust(subset(pointsUXO15555, select = c(2:4)), k=10,

Hello everyone I tried to use clust function using "hclustWard" clustering method The distance mesaured I have used is "rf" The data used is in the form of data frame (it is not a distance matrix) - sd.df The piece of code I have used is: c1 <- clust(sd.df,k=6,method="hclustWard",distMethod="rf") But I get the following error message, Error in if (n

Hi, I have date and time in a format like this: " 2007-02-21 05:19:00". Do you which function i can use to derterminate the difference in time between this value and an other one. For exemple: this one : 2007-02-21 05:19:00 and this one : 2007-02-20 14:21:53 Thanks a lot, Karine H. _________________________________________________________________

Hi, I am using the nls function and it stops because the number of iterations exceeded 50, but i used the nls.control argument to allow for 500 iterations. Do you have any idea why it's not working? fm1 <- nls(npe ~ SSgompertz(npo, Asym, b2, b3), data=f,control=nls.control(maxiter=500)) Thanks for your help, Cheers, Karine.

Hi, I am using the nls function and it stops because the number of iterations exceeded 50, but i used the nls.control argument to allow for 500 iterations. Do you have any idea why it's not working? fm1 <- nls(npe ~ SSgompertz(npo, Asym, b2, b3), data=f,control=nls.control(maxiter=500)) Error in nls(y ~ exp(-b2 * b3^x), data = xy, algorithm = "plinear", start = c(b2 =

Hi everybody, I am using the contour function to draw isobares. And i would like to to bold contours for an interval of 500m and weak contour for an interval of 100m. Can someone help me with this? Thanks a lot Karine _________________________________________________________________ [[elided Hotmail spam]] [[alternative HTML version deleted]]

Dear R users, I'd like to ask u whether you know how to sort out the following: I'm trying to reproduce a dataset of clusters, and for that I need to build up a cluster index (inside a function) using the command "replicate" as follows: dataset<- function( clusters=100, cluster.size=50, outcome.mean=list(mean=3, sd=1), outcome.var=list(mean=0, sd=1), treat=1, unbal =

Dear list, I have two dissimilarity matrices, one for a training data set which I then clustered using PAM. The second is a diss matrix for a validation data set (an independent field sample). I have been trying to use knn to distinguish distances between the validation data set and the 6 mediods of the training data defined by using PAM. I continue to get error messages in regards to either the

Hi I've created a file in users GPO and put it in start script. It contains the following statements : C:\Windows\System32\reg.exe delete HKEY_CURRENT_USER\Software\Microsoft\Windows\CurrentVersion\Run /v OneDrive /f C:\Windows\System32\reg.exe delete HKEY_CURRENT_USER\Software\Microsoft\Windows\CurrentVersion\Run /v com.squirrel.Teams.Teams /f I've the following result with gpresult (in

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Hello, The following code does'nt work for me. The last command reports an error. I have created a consensus tree using the consensus comand from phylo but cannot manipulate the phylo object afterwards to create a dendogram , by transforming the phylo object into a hclust object and then into a dendogram ?? Thanks for any help library(ade4) library(cluster) library(stats) library(ape)

Hi R-helpers I have a dataframe DF (lets say with the variables, y, x1, x2, x3, ..., clust) containing relatively many NAs. When I fit an ordinal regression model with the function lrm from the Design library: model.lrm <- lrm(y ~ x1 + x2, data=DF, x=TRUE, y=TRUE) it will by default delete missing values in the variables y, x1, x2. Based on model.lrm, I want to apply the robust covariance

Hello, I have a large data set that has more columns than rows (sample data below). I am trying to perform a partitioning cluster analysis and then plot that using pca. I have tried using CLUSPLOT(), but that only allows for 'princomp' where I need 'prcomp' as I do not want to reduce my columns. Is there a way to edit the CLUSPLOT() code to use 'prcomp', please? #

Problem with join to Active Directory [root@clust-master samba]# net ads join -S 10.0.0.1 -U Administrator Administrator's password: [2006/05/22 10:24:05, 0] libads/ldap.c:ads_join_realm(1640) ads_add_machine_acct (clust): Type or value exists ads_join_realm: Type or value exists [root@clust-master samba]# kinit Administrator@COROD.LOCAL Password for Administrator@COROD.LOCAL: As you can

Dear all, I generated a heatmap with the heatmap() function with the default "complete" linkage method, but when I add the argument Rowv=as.dendrogram(hclust(dist(matrix), method="complete")), The dendrogram generated is different from the dendrogram produced by heatmap() with default settings. Could someone kindly point out where my mistakes are? P.S. When I did