similar to: Calculating cumulative lengths of hierarchical topology

Please also check for the proper security context. Do ls -Z /var/www/html/index.html. The context type httpd_sys_content_t should be present. Regards 2015-05-08 14:32 GMT+02:00 Richard <lists-centos at listmail.innovate.net>: > More specifically -- when you get the "not found" in the browser > there should be an entry logged in the error log. E.g., tail the > error log,

More specifically -- when you get the "not found" in the browser there should be an entry logged in the error log. E.g., tail the error log, issue a request, and see what you see. The error log entry will show the details of what is being requested and generally gives strong hints as to why it can't be found (pathing, access, etc.). If you don't get an entry in the error log that

Dear All, I'm trying to read a text data file that contains several records separated by a blank line. Each record starts with a row that contains it's ID and the number of rows for the records (two columns), then the data table itself, e.g. 123 5 89.1791 1.1024 90.5735 1.1024 92.5666 1.1024 95.0725 1.1024 101.2070 1.1024 321 3 60.1601 1.1024 64.8023 1.1024 70.0593

Hi, I''m using heatmap.2 to cluster my data, using the centroid method for clustering and the maximum method for calculating the distance matrix: library("gplots") library("RColorBrewer") test <- matrix(c(0.96, 0.07, 0.97, 0.98, 0.50, 0.28, 0.29, 0.77, 0.08, 0.96, 0.51, 0.51, 0.14, 0.19, 0.41, 0.51), ncol=4, byrow=TRUE)

Dear Dr. Liaw Andy: I have a few more questions about your heatmap function. actually heatmap is what I am looking for. heatmap(x, Rowv, Colv, distfun = dist, hclustfun = hclust, add.expr, scale=c("row", "column", "none"), na.rm = TRUE, ...) my data is a XNEW, > dim(XNEW) [1] 554 335 554 genes, 335 samples. now I want to use 1-CORR as a distance

I'm parallelizing some computation on hierarchical data, and would find it natural to do something like this (where a call to parLapply is embedded in outer call to parLapply): cl <- makeCluster(rep.int('localhost', 5), type='SOCK') clusterExport(cl, 'cl') parLapply(cl, 1:5, function(i) parLapply(cl, 1:5, function(j) i * j)) Snow

hi, I want to do hierarchical clustering with Jaccord index. I tried to do with vegan package for finding index and hierarchical clustering with hclust function. While doing clustering it is showing an error message as "invalid distance method". I would be grateful if anyone tells how to rectify the error. Thanks in advance,   kind regards, Ms.Karunambigai M PhD Scholar Dept. of

Addendum: I tried a gamma fit in glmmPQL and got the same errors. *Ben Caldwell* PhD Candidate University of California, Berkeley On Tue, May 17, 2011 at 3:51 PM, Benjamin Caldwell <btcaldwell@berkeley.edu>wrote: > Hello > After seeing this ( > https://stat.ethz.ch/pipermail/r-sig-mixed-models/2011q1/005213.html) email > I thought I would check the issue with a gamma family

> From: Martin Devera <devik@cdi.cz> > Subject: [LARTC] (E)SFQ suggestion > Hi, > just simple note. Maybe it is already in progress :) > > There are attempts to replace hashing routine in SFQ to > consider IPs or ports. > What about to use HRR - roundrobin around bunch of IP > adresses and then smaller WRR for ports per IP ? > It would solve both

Hi, I have some hydrochemical data from observation stations of a river network. The data set provides information about the river hierarchy, i.e. the order of the rivers (main river is 1st order, contributing is 2nd order, and contributing to 2nd is 3rd order... etc). Now I would like to use the hierarchical information to: a) plot a dendrogram of the observation stations b) perform some simple

While trying to dodge issues with case-sensitivity, I stumbled on a somewhat effective solution: the old Mac OS Hierarchical File System (HFS). HFS is case insensitive and supports symlinks, making it very useful for Wine. The drawbacks are that it's slow compared to modern file systems, the max file size is 2GB and filenames are limited to 31 bytes. It will likely have problems running

Dear R-helpers, Is there somebody who knows if R has already a build in function for Hierarchical Clustering which uses Mutual Information as proximity measure? Many thanks and best regards, J. --------------------------------- [[alternative HTML version deleted]]

Dear experts, I would like to plot a hierarchical clustering of 300 items. I had a distance matrix with dimension of 300*300. The 300 items were from 7 groups which I would like to label with 7 different colours in the plot. > h<-hclust(as.dist(300_distance_matrix)) > plot(h,hang=-1,cex=0.5, col="blue") I used the above script to plot the result. The cluster was all blue,

Hi, I'm having difficulty to replicate in R a nested (hierarchical) anova example found in p. 308 of Zar, J.H. 1996. Bostatistical Analysis. Prentice Hall. 3rd ed. The example (15.1) is as follows: The variable is blood cholesterol concentration in women (in mg/100 ml of plasma). This variable was measured after the administration of one of three different drugs, each drug having been

Hi R users! I have a bit of a problem with using an hierarchical clustering algorithm: a<-c(1:15) b<-rep(seq(1:3), 5) c<-rnorm(15, 0,1) d<-c(sample(1:100, 15, replace=T)) e<-c(sample(1:100, 15, replace=T)) f<-c(sample(1:100, 15, replace=T)) data<-data.frame(a,b,c,d,e,f) q<-data.frame(data$d, data$e, data$f) q<-scale(q) What i want to do is to use an

Let's say I have data in the following schema that describes the number of purchases a company has received from each County in the US: State | County | Purchases --------------------------------------- NJ | Mercer | 550 CA | Orange | 23 .... I would like to visualize what states contribute the most to the overall total, and furthermore within those states, what Counties contribute the most.

I think are looking for the function 'cutree' from package mva checkout its documentation: > require(mva) > ?cutree pleanty of examples to do what you want. ############################################################################# Hi R lovers! I am using the agnes function of the package cluster to compute a hierarchical clustering. I'd like to know if somebody has ever

I would like to get an hierarchical clustering tree with bootstrap values indicated on the nodes, as in pvclust. The problem is that I have only distance matrix instead of the raw data, required for pvclust. Is there a way to get it? fit1 <- hclust(dist) # an object of class '"dist" plot(fit1) # dendogram without p values library(pvclust) fit2 <- pvclust(raw.data,

Hi, i have the following problem: I am using k-means algorithm for clustering. But instead of using randomized centers, I would like to use centers created by hierarchical clustering. So I want to apply "hclust" on my data set (in this case the iris data), getting a solution by "cutree", calculating the means/centers of the resulting clusters and use these centers as starting

Hi I would like to run a multi-level hierarchical logistic regression model with sampling weight? Is this possible with R? Thanks a lot, Qian Guo --------------------------------- [[alternative HTML version deleted]]