search for: stressing

Hi, I am trying to create 3 mds plots: one with axis 1 vs axis 2, one with axis 2 vs axis 3, and one with axis 1 vs axis 3. When inputting my code, I only end up with one diagram and when inputting mdsg.mds$dims, the program returns 2 for 2 dimensions. How can I create the other two plots? Any help would be greatly appreciated, Calla Carbone The table I use is number of each taxa on each

Hi LLVM, I'm currently setting up some tools to investigate the influence of the order of optimization passes on the performance of compiled programs -nothing exceptional here. I noticed something inconvenient with opt, namely that splitting a call does not always give the same output: % llvm-stress > stress.ll % opt -dse -verify -dce stress.ll -o stress-1.bc % opt -dse stress.ll |

Dear All, I am working with linear mixed-effects models using the lme4 package in R. I created a model with the lmer function including some main effects, a two-way interaction and a random effect. Now I am searching how I could incorporate an interaction between the random effect and one of the fixed effects. I tried to express the interaction in:

Hi Eli, Unfortunately the differences remain, I do not observe a significant change in the output besides the fact that it's random. I noticed that running opt without options on the random file changes the order of references in the predecessors of basic blocks (sample below). Further invocations of opt are idempotent. I don't know of this information is stored in the bytecode file

I'm not sure this list is the right place for this thing. I noticed some erratic behaviour in sammon(). Running sammon on two nearly identical sets of data results in very different results. Below is an example. I create an initial configuration with cmdscale() and store it into 'vec1'. I write this to file, and read it back in again to 'vec2'. According to cor() on the three

Hi, I want to know whether there is any function in R to find STRESS after using cmdscale and estimating the coordinates, I have written these functions to find stress (for p =1,2,3,4,5) stress<-rep(0,5) for(p in 1:5) { datahat<-cmdscale(d,p) deltahat<-as.matrix(dist(datahat)) a<-0 b<-0 for(i in 1:n) { for(j in 1:n) { a<-d[i,j]^2+a b<-(d[i,j]-deltahat[i,j])^2+b } }

What objective function is maximized by survreg with the default Weibull model? I'm getting finite parameters in a case that has the likelihood maximzed at Infinite, so it can't be a simple maximum likelihood. Consider the following: ############################# > set.seed(3) > Stress <- rep(1:3, each=3) > ch.life <- exp(9-3*Stress) > simLife <- rexp(9,

Hi R-Help! My question: I have lifetime/failure data of machines with different stress levels and i think an weibull/extreme value distribution would fit this data. So I did: model1 <- survreg(Surv(lfailure)~stress,data=steel,dist="extreme") (where lfailure=log(failure)) Now I would like to do a likelihood ratio test to test the hypothesis H0: location parameters of the

Hi Mehdi, Thank you for mentioning this tool, I was looking for something like this. By default the analyzer produces identical output on both files, but a complete -dump shows that the storage order of the symbol table is different. This would explain why text files are not affected: the symbols are used directly in text form so there is no need for this table. I suppose that settles the

I''m experimenting with xen + iscsi, and I founded that under heavy stress domU''s can crash entire system, I''ve reproduced this many many times. My system is like this Software: - iSCSI Enterprise Target v0.4.13 - RedHat AS4 update 4 64bit + Xen 3.0.3-0 Kernel 2.6.16.29 + Open iSCSI v2.0.730 (Initiator) - Bonnie++ v1.03a VM: - Debian 3.1r3 + Open iSCSI v2.0.730

Hello, We are trying to find a function to compute "stress" in our multidimensional scaling analysis of a dissimilarity matrix. We've used "dist()" to create the matrix and "cmdscale()" for the scaling. In order to determine the number of dimensions we would like to plot stress vs. dimensions. However, we cannot find a pre-made command. It seems that other

Hi all, I try to calculate the stress of a configuration using the formula in the isoMDS help, but I don't have the same result than the stress returned by isoMDS : > library(mva) > library(MASS) > data(swiss) > swiss.x <- as.matrix(swiss[,-1]) > swiss.dist <- dist(swiss.x) > swiss.mds <- isoMDS(swiss.dist) initial value 2.979731 iter 5 value 2.431486 iter 10

Among those users of Primer, stress values greater than 0.3 are interpreted as "questionable". Using both isoMDS and metaMDS (vegan package), the stress values returned are much higher using my own data and using examples provided in R Help. For example Rstress = 8.3, and the stressplot r2 = 0.99 indicating (to me) that the ordination is OK. I am guessing that the "stress"

Hello, I have a data set on which I run the sammon algorithm as follows: library(MASS) data = read.table('problemforr.dat') y = cmdscale(data, add=TRUE) s = sammon(data, y$points) (In case it should be relevant, I make the data available at http://idi.ntnu.no/~edsberg/problemforr.dat) With R 2.2.1 on Debian Sid I always get one of two solutions (stress 1.74288 after 10 iterations or

Hi, I am looking for the best multidimensional configuration for my data (47*47 distance matrix). I ve tried classical metric (cmdscale) and non metric MDS (isoMDS, nmds) but it is now difficult to choose the best solution because of the uncertainties in the definitions of the "stress" function. So, same problem, several questions : 1. Statistical consideration : With

Dear useRs, last week I asked you about a problem related to isoMDS. It turned out that in my case isoMDS was trapped. Nonetheless, I still have some problems with other data sets. Therefore I would like to know if anyone here has experience with how well isoMDS performs in comparison to other non-metric MDS routines, like Minissa. I have the feeling that for large data sets with a high

Hi All, I was wondering, what tools are readily available out there in Asteriskland for me to use in stress/load testing asterisk box I have in the lab. I want to observe how my box holds out under heavy/light/medium load. Thanks, Jeng ___________________________________________________________ Want ideas for reducing your carbon footprint? Visit Yahoo! For Good

I could do this in various hacky ways, but what's the right way? I have a nice application of the by function, which does what I want. The output looks like this: > auc_stress lab.samples.stress$subid: 2 cortisol amylase 1 919.05 6834.8 ---------------------------------------------------------------------------------------------------------------------------

We are in the process of implementing realtime voicemail. I was wanting to "stress-test" the system to see if or when it would fall over. Is it possible to use sipp to create say 250 calls, each of which leaves a message in the voicemail ? My dialplan is currently [default] exten => stress,1,Answer() exten => stress,2(vm),Voicemail(7777|su) exten => stress,3,Hangup()

Hi, How can I stress test an asterisk IVR? I am looking for some kind of sip phone which can be "programmed" to send out digits after specified time to simulate users pressing menu items. If it can originate large number of calls simultaneously then it's great! Does any one have any recommendations ? Any other method to stress test an IVR call flow? with regards, raj