similar to: problems while correlating values

I have 4 dell 2970 server , three server harddisk is 146Gx6 ,one hard disk is 72Gx6: each server mount info is /dev/sda4 on /exp1 type xfs (rw) /dev/sdb1 on /exp2 type xfs (rw) /dev/sdc1 on /exp3 type xfs (rw) /dev/sdd1 on /exp4 type xfs (rw) /dev/sde1 on /exp5 type xfs (rw) /dev/sdf1 on /exp6 type xfs (rw) I create a gluster volume have 4 stripe gluster volume create test-volume3 stripe 4

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)

I did a correlation for the values - EX4577 EX4599 EX4566 EX4522 WL917 2.53528 0.79077 0.21499 -0.01084 WP429S -0.192723715 WP819 -1.016997552 WP977 1.378674 -0.07071 0.625089 0.4728363 WI205S -0.24443 -1.789526 0.648923 -0.775867 by using round(cor(t(person.data),use="pairwise.complete.obs")) i got the result as - WL917 WP429S WP819 WP977 WI205S WL917 1 NA NA

Good day, For lack of a better solution (or perhaps I am ignorant to something more elegant), I have been bootstrapping panel data by hand so to speak and I would like to know if there is a way to define multiple variables in a loop using the loop variable. I found a post (here: https://stat.ethz.ch/pipermail/r-help/2002-October/026305.html ) that discussed naming multiple variables but it

Hi, i have a dataframe such as: Exp1 Exp2 Exp3 name1 12.6 78.0 45.6 name2 11.9 19.0 21.0 name3 10.0 14.0 17.0 ... ... ... Real datasets might be quite large - 20,000 rows by 100 columns I want to calculate metrics such as the variation *row-wise*. So, var for name1, var for name 2, var for name3 etc. Can someone kindly guide me on how best to code this? Also, once such a metric has

I need to be able to detect a well-behaved loop. (i.e one where exp1 assigns a value to an int i, exp2 compares i with a loop constant, exp3 adjusts i by a loop constant, and the inner block has no assignments to i.) I need this because in Sun's Java VM garbage collection only takes place at safepoints, so a potentially unbounded loop must call safepoint() some time. However, safepoints are

below is a code to compute hessian matrix , which i need to generate 29 number of different matrices for example first element in x1 and x2 is use to generate let say matrix (M1) and second element in x1 and x2 give matrix (M2) upto  matrix (M29) corresponding to the total number of observations and b1 and b2 are constant.  can some one guide me or help to implement this please. I did not

Dear Sirs, I am using both the Bioconductor adds on (Affy, AffyPLM,...) and the 'standard' R-package. I am trying to select a list of genes which all have expression values below a certain threshold. I have done this by creating a vector which has 0s where the expression is greater than the threshold and 1s where it is less than or equal to it. Multiplying this vector by the expression

Please use an informative subject for sake of the archives. Here are several solutions: aggregate(DF[4:8], DF[2], mean) library(doBy) summaryBy(x1 + x2 + x3 + x4 + x5 ~ name, DF, FUN = mean) # if Exp, name and id columns are factors then this can be reduced to library(doBy) summaryBy(. ~ name, DF, FUN = mean) library(reshape) cast(melt(DF, id = 1:3), name ~ variable, fun = mean) On

Dear all, I have a dataset Exp name id x1 x2 x3 x4 x5 1 a 1 23 24 23 22 30 1 b 2 25 26 27 23 24 1 c 3 32 19 23 25 28 2 a 4 28 32 24 26 27 2 b 5 23 24 25 26 28 2 c 6 23 31 30 38 23 3 a 7 24 25 31 27 29 3 b 8 28 25 26 32 28 3 c 9 21 31 28 23 29 where each name a,b and c is repeated three times. Now I want to calculate the the averages of

Dear R-helpers, I am trying to check whether a model of the form y(t) = a/(1 +b*t) fits the curve of downloads per day of a file in a specific online community better than a model of the form y(t) = a*exp(-b*t). For that, I used nls to fit both models and I am now trying to compare the fits with anova. The problem I find is that anova does not report an F statistic or a p-value when I compare

Hi @ all, I hope for some help of you. I have a dataframe and I want to regroup it. examp4.csv <http://r.789695.n4.nabble.com/file/n4648927/examp4.csv> I need the arguments of "VAL" as table heads and the "TYPE " only in individual expression. The result should look like in the example pic. exp4.png <http://r.789695.n4.nabble.com/file/n4648927/exp4.png> I

Hello everybody, I need an help because I don´t know if the command for the ANOVA analysis I am performing in R is correct. Indeed using the function aov I get the following error:"In aov (......) Error() model is singular" The structure of my table is the following: subject, stimulus, condition, sex, response Example: subject stimulus condition sex response

Dear all, I would like to know if it?s possible to create an index for a variable/vector that specifies the value in the n position before the actual value. For example, if X <- c(letters[1:10]), x[10] is ?j?. I would like to create an index exp3 (the third position before) such as if z <- x[exp3], then z[10] = ?g?. In Stata that index is x[-3], but not in R. I have to input it in a very

Hi, I have a dataset saved in *.csv format, that contains 13 columns (the first column being the title name and the rest experiments) and about 2500 rows. Not all columns in the row have data in it i.e for eg BS00,-0.084,0.0136,-0.1569,-0.6484,1.103,1.7859,0.40287,0.5368,0.08461,-0.1935,-0.147974,0.30685 BS01,0.491270283,0.875826172,,,,,,,,,,

Dear R experts, I would like to please ask for your help with repeating steps in an apply statement. I have a dataframe that lists multiple variables for a given id and visit, as well as drug treatment. > head(exp) id visit variable1 variable2 variable3 variable4 drug 1 3 1 13 10 7 11 0 2 3 5 10 15 9 9 0 3 3 12

OK, this is really weird! here's an example code: t1<-c(1,2,3,4) t2<-c(4,2,4,2) plot(t1~t2, xlab="exp1", ylab="exp2") dev.copy2eps(file="test.eps") that all seems fine... until you look at the eps file created, where for some weird reason, if you scroll down to the end, the code reads: /Font1 findfont 12 s 0 setgray 214.02 18.72 (e) 0 ta -0.360 (xp1) tb

All, I have been able to successfully use the optim( ) function with "L-BFGS-B" to find reasonable parameters for a one-compartment open pharmacokinetic model. My loss function in this case was squared error, and I made no assumptions about the distribution of the plasma values. The model appeared to fit pretty well. Out of curiosity, I decided to try to use nlminb( ) applied to a

Hello, I ran two lme analyses and got expected results. However, I saw something suspicious regarding p-level for fixed effect. Models are the same, only experimental designs differ and, of course, subjects. I am aware that I could done nesting Subjects within Experiments, but it is expected to have much slower RT (reaction time) in the second experiment, since the task is more complex, so it

Processing commands for control at bugs.debian.org: > # bts housekeeping - fixing up versions to enable automatic bug archival > notfound 706747 3.2p1.4-28.1 Bug #706747 {Done: Andreas Beckmann <anbe at debian.org>} [olvwm] olvwm: fails to install [i386]: update-alternatives: error: alternative path /usr/bin/X11/olvwm-x-window-manager doesn't exist. There is no source info for the