search for: denning

Howdy, I've got a CentOS 7 VM that occasionally becomes unresponsive. There's a "list_add corruption" entry in /var/log/messages, included below. This is on VMware. We have lots of other VMs which are running just fine. Only a few are CentOS 7 VMs, though, so I can't rule out some kind of environment issue. It's up-to-date on OS patches, and running kernel

Dear all, I created a bivariate normal distribution: set.seed(138813) n<-100 x<-rnorm(n); y<-rnorm(n) and plotted a scatterplot of it: plot(x,y) Now I'd like to add the 2D-standard deviation. I found a thread regarding plotting arbitrary confidence boundaries from Pascal H?nggi http://www.mail-archive.com/r-help at r-project.org/msg24013.html which cites the even older thread

In the following code, the only difference between the two plots is the order the variables are plotted. In this case, the plot of "cdata.den" in plot #1 is different from its plot in #2. Specifically, "cdata.den" spans the x-axis from -5 to 30 in plot #1 and from 0 to 20 in plot #2. Does anyone understand why these two plots do not yield the same result? #Make density

Hi All, I have a for loop inside the function and I cannot get UUU to give me an updated grid.dens object when I run the function (it does update when I run just the for loop). Here's a simplified version of my function: UUU=function(pop, grid.dens) { for (i in 1:10){ Food=grid.dens[pop$yloc[i],pop$xloc[i]] #use initial grid.dens values Consumed=(pop$weight[i]*0.25) Left=Food-Consumed

Dear R users, This is a KDE beginner's question. I have this distribution: > length(cap) [1] 200 > summary(cap) Min. 1st Qu. Median Mean 3rd Qu. Max. 459.9 802.3 991.6 1066.0 1242.0 2382.0 I need to compute the sum of the values times their probability of occurence. The graph is fine, den <- density(cap, from=min(cap), to=max(cap), give.Rkern=F)

Greetings all; I've probably got something miss-configured, but I have an intermittent smbd problem, where it will use 15% or so of this machine and nearly all the much slower firewall box. I'll try to give enough data here, so my apologies about the length of this post. The installed samba versions on this very heavily patched RH8.0 machine are: --- [root@coyote root]# rpm -qa|grep

Hello, My name is Craig and I need help plotting a "line" for a multiple linear regression in R. Here is my sample data (filename: convis.txt) Output of convis.txt is (vis and density being predictors of either avoidance or entrance): vis den avoid entrance 1 10 1 0.0000 0.0000 2 10 3 0.8750 0.0000 3 8 3 0.8180 0.0300 4 8 3 0.6670 0.0667 5 8 1

Hello All, I have a panel date - here a small-scale example: df <- data.frame(cbind(rep(c("AUT","BEL","DEN","GER"),4),cbind(rep(c(1999,2000,2001,2002),4)),sample(10,16,replace=T))) names(df) <- c("country","year","x") SORT <- c("GER","BEL","DEN","AUT") I need to compute the

Hello, I'm trying to use the bam() function in the R mgcv package for a large set of grouped binary data. However, I have found that this function does not take data in the format of cbind(numerator, denominator) on the left hand side of the formula. As an example, consider the following dat1 <- data.frame(id=rep(1:6, each=3), num=rbinom(18, size=10, prob=0.8), den=rbinom(18, size=5,

I got this figured out much faster than I thought I would. Thanks to all of your help, Peter, Mattias, Thomas and Helmut. And Thomas, that 8 partition live OS sounds right up my alley, and I will definitely check it out. The second partition is working well with `parted' and `fdisk', so I am quite pleased. Below is, again, "what I came up with". I tried to integrate each of your

Dear developers, the current implementation of hist.default() calculates 'density' (and 'intensities') as dens <- counts/(n*h) where h has been calculated before as h <- diff(fuzzybreaks) which results in 'fuzzy' values for the density, see e.g. > tmp <- hist(1:10,breaks=c(-2.5,2.5,7.5,12.5),plot=FALSE) > print(tmp$density,digits=15) [1]

Hi, I'm using the densCols function for a scatterplot and cannot figure out 1) how to extract the computed densities, and 2) how to create a legend based that represents the upper and lower ranges of the densities. For example: movers.den <- densCols(move$x, move$y) table(movers.den) #08306B #083775 #083B7C #083D7E #3989C1 #3F8FC4 28 22 101 25

Dear Users, I have one problem here, I tried many time and even read a few notes on writing function but still..... Can anyone help me on how to simplify Part B (please refer the programming below), so that I don't have to repeat the calculation of "num" and "r" ? Thank you very much..every help is very much appreciated... ## Part A n=1400 m=matrix(c(0,0,0,0),4,1)

In The American Statistician vol 42 (1988) pages 257 - 280, Yoav Benjamini investigates some variations on the box plot, including vaseplots, which maek the width of each box vary proportionally to he estimated density at a particular point. Has anyone implemented these in R ? Thanks as always Peter

Hi all, I've got a density graph made with the following commands: win.graph(width=13,height=6) par ( fin=c(13,3) ,mai=c(1,1,0.5,0.5) ,mfrow=c(1,2) ,cex.axis=1.5 ,cex.lab=1.5) dens<-density(DATA1.y[2,]-mean(DATA1.y[2,]),kernel="gaussian") xlimit<-range(dens$x) ylimit<-range(dens$y) hist( DATA1.y[2,]-mean(DATA1.y[2,]) ,xlim=1.1*xlimit ,xlab=expression(q[e])

Dear Rhelpers I have the problem with initial values, could you please tell me how to solve it? Thank you June > p = summary(maxLik(fr,start=c(0,0,0,1,0,-25,-0.2))) Error in maxRoutine(fn = logLik, grad = grad, hess = hess, start = start, : NA in the initial gradient > p = summary(maxLik(fr,start=c(0,0,0,1,0,-25,-0.2),method="BFGS")) Error in optim(start, func, gr =

So i successfully upgraded my Debian vm''s to Debian 6 on XCP 1.0, but when i try to install a new clean one it always fails. Why is this? The VM won''t even start, while i used the Debian 6 squeeze template. Is this even possible? Thanks, Peter _______________________________________________ Xen-users mailing list Xen-users@lists.xensource.com

Hai - kann mir jemand sagen, wie ich den Modalwert in R berechne?! IRgendwie finde ich den Befehl nicht.... greetz und herzlichen Dank Sonja

Hi there, Does anyone know how to extract elements from the table returned by Manova()? Using the univariate equivalent, Anova(), it's easy: a.an<-Anova(lm(y~x1*x2)) a.an$F This will return a vector of the F-values in order of the terms of the model. However, a similar application using Manova(): m.an<-Manova(lm(Y~x1~x2)) m.an$F Returns NULL. So does any attempt at calling the

I?m working on an R-implementation of the simulation-based finite-sample null-distribution of (R)LR-Test in Mixed Models (i.e. testing for Var(RandomEffect)=0) derived by C. M. Crainiceanu and D. Ruppert. I'm in the beginning stages of this project and while comparing quick and dirty grid-search-methods and more exact optim()/optimize()-based methods to find the maximum of a part of the