similar to: R function, sink() and empty file

I have these 3 models. class Ivr < ActiveRecord::Base has_many :klusterings, :dependent => :destroy has_many :klusters, :through => :klusterings, :uniq => true end class Kluster < ActiveRecord::Base has_many :klusterings, :dependent => :destroy has_many :ivrs, :through => :klusterings, :uniq => true end class Klustering < ActiveRecord::Base belongs_to :kluster

I've developed a web application in PHP and R my script is <?php ... exec("R CMD BATCH --silent /home/marcello/R_in/myfile.bat /home/marcello/R_out/myfile.out"); ... ?> This script execute in R batch mode and write the myfile.out. On Win2000 the similar script is ok, but on linux I've a problem. I suppose is a permession problem because the same script on shell

Dear all, sorry for this very basic question, but I did not find any good example yet. I would like to set up a variable that can be recall later to substitute a part of a file name. As example: var_filename = as.name("aaa") jpeg("var_filename.jpg") plot() dev.off() It would be very useful in order to avoid to change manually many strings. I guess it is possible, but I did

Dear list, I have to compare two digital elevation models in raster format (geotiff). I then have to calculate the differences in altitude for each cell and make some statistics (basic as mean, median, std, range but also more "advanced" as RMSE) on that. I do not know very much how to proceed: 1) is it possible to import the geotiff in R? If so with which package? if not which is the

Estimados Escribo para consultar sobre el uso de modelos mixtos anidados. Los datos que estoy analizando provienen de censos de malezas en cuatro tipos de paisajes de la región pampeana, en los que seleccioné al azar igual número de lotes agrícolas cultivados con tres cultivos (maíz, soja y trigo-soja). En cada lote censé el número de especies de malezas en tres posiciones: el alambrado, el borde

Dear list, I just tried to use the function cluster.stat in the package fpc. I just have a couple of questions about the syntax: cluster.stats(d,clustering,alt.clustering=NULL, silhouette=TRUE,G2=FALSE,G3=FALSE) 1) the distance object (d) is an object obtained by the function dist() on my own original matrix? 2) clustering is the clusters vector as result of one of the many clustering methods?

Dear Lists, I try to configure Samba as PDC LDAP backend with Linux-Suse-9.1 and smbldap-tools form www.idealx.org, I follow guide from SMB-3 by Example book. Step by step installation and configuration came with no error. except i couldnt join w2k workstation to the new domain with administrator account. # /var/lib/samba/sbin/smbldap-usershow administrator dn:

I've developed a web application in PHP and R my script is <?php ... exec("R CMD BATCH --silent /home/marcello/R_in/myfile.bat /home/marcello/R_out/myfile.out"); ... ?> This script execute in R batch mode and write the myfile.out. On Win2000 the similar script is ok, but on linux I've a problem. I suppose is a permession problem because the same script on shell

Now I have some access problems. This is what ends up un messages Hosts.allow is set to accept anyone on the local net. Username and passwords are the same Upsc gives proper output. System is Centos 6.8 Jul 22 17:20:06 BIFROST upscode2[10113]: Startup successful Jul 22 17:20:06 BIFROST upsd[10116]: listening on ::1 port 3493 Jul 22 17:20:06 BIFROST upsd[10116]: listening on 192.168.0.1 port 3493

Is the primary difference between the current version download (e.g., 2.15.1) and the "patched" download of these R files that the patched files have NOT been verified? Please confirm and thanks! [[alternative HTML version deleted]]

Hi there, I have just started using the MASS package in R to run M-estimator robust regressions. The final output appears to only give coefficients, degrees of freedom and t-stats. Does anyone know why R doesn't compute R or R-squared and why doesn't give you any other indices of goodness of fit? Does anyone know how to compute these in R? Sophie -- View this message in context:

On Sat, Jul 22, 2017 at 7:48 AM, Charles Lepple <clepple at gmail.com> wrote: > > I also have not used a Synology device, but as I recall, they generally > expect to be the NUT master system. This may cause problems if you need to > do something fancy with upssched. > The Synology boxes work fine as NUT clients, *however* they provide very little ability to configure NUT

Hello All, I'm having some trouble figuring out what the clearest way to plot my k-means clustering result on an my existing MDS. First I performed MDS on my distance matrix (note: I performed k-means on the MDS coordinates because applying a euclidean distance measure to my raw data would have been inappropriate) canto.MDS<-cmdscale(canto) I then figured out what would be my optimum

Regarding a previous question concerning the kmeans function I've tried the same example and I also get a strange result (at least according to what is said in the help of the function kmeans). Apparently, the function is disregarding the initial cluster centers one gives it. According to the help of the function: centers: Either the number of clusters or a set of initial cluster

Hi all, I am trying to run the k-means cluster analysis using the function kmeans in the package cluster. The data are: x = c(-0.26, -0.23, -0.05, -0.20, 0.30, -0.84, -0.10, -0.12, 0.10, -0.31, -0.19, 0.18, -0.26, -0.23, -0.37, -0.23) I've got two different solutions when I ran this function over a few times: kmeans(x, centers=2) The first solution gives the following: $cluster [1]

Hi Team, I am trying to run kmeans in R, and I need to save the different clusters into different folders. How can I achieve this? # this is how my data looks. $ *cat 1.tsv | head* userid bookid rating bookTotalRatings bookAvgRating userTotalRatings userAvgRating 1 100 0 24 2.7916666666666665 291 2.6735395189003435 2 200 7 24 2.9583333333333335 6 7.0

Hi, I am using kmeans to cluster a dataset. I test this example: > data<-matrix(scan("data100.txt"),100,37,byrow=T) (my dataset is 100 rows and 37 columns--clustering rows) > c1<-kmeans(data,3,20) > c1 $cluster [1] 1 1 1 1 1 1 1 3 3 3 1 3 1 3 3 1 1 1 1 3 1 3 3 1 1 1 3 3 1 1 3 1 1 1 1 3 3 [38] 3 1 1 1 3 1 1 1 1 3 3 3 1 1 1 1 1 1 3 1 3 1 1 3 1 1 1 1 3 1 1 1 1 1 1 3

I'm doing kmeans partitioning on a small (n=26) dataset that has 5 variables. I noticed that if I repeatedly run the same command, the cluster centers change and the cluster membership changes. Using RW1022 under Windows NT & Windows 2000 >kmeans(pottery[,1:5], 4, 20) [...snip] $size [1] 7 3 9 7 [...snip] $size [1] 7 10 4 5 [...snip] $size [1] 6 10 5 5 yields a different

Wiindows XP R 2.7 I am using sink() to send the results of my analyses to a text file. Unfortunately my graphs do not become part of the file. Is there anyway that I can have both the text and graphic output of my analyses appear in a file? Thanks, John John David Sorkin M.D., Ph.D. Chief, Biostatistics and Informatics University of Maryland School of Medicine Division of Gerontology Baltimore VA

Dear members. I am having problems to understand the kmeans- results in R. I am applying kmeans-algorithms to my big data file, and it is producing the results of the clusters. Q1) Does anybody knows how to find out in which cluster (I have fixed numberofclusters = 5 ) which data have been used? COMMAND (kmeans.results <- kmeans(mydata,centers =5, iter.max= 1000, nstart =10000)) Q2) When I