similar to: Update: Dynamic Memory Allocation Errors in 1.2.0?

Let me first say I'm new to R and new to this mail list, so I apologize ahead if this issue has already been discussed here. The dynamic memory allocation of 1.2.0 seems to be an improvement over the static allocation of 1.1.1. However, I have run across at least one case where the dynamic allocation might be corrupting my results. I am interested in calculating the 95% confidence margins of

I have noticed a definite loss of numerical precision going from 1.1.1 to 1.2.x under both Windows 98 and NT4 on x86 architecture. I noticed the difference when using the abcnon() function in the bootstrap package, but I think you could see the problem in any routine that involves subtracting relatively large numbers from each other. For the case I am looking at (see code below), the abcnon

Dear R-Users, I have a large number of data(54000) and the field of data is 50 to 2.0e9. I want to use normalmixEM (package:mixtools) to fit them in finite mixture narmal distributions,but get some mistakes.I don't know which steps make the error. I have used the following functions before >x<-read.table("data") >log.x<-log10(x$V1) >log.x<-sort(log.x)

I've just built R 2.9.2 from source on Slackware Linux 13.0 - 32-bit (will try 64-bit also next) - and seen: > Collecting examples for package 'stats' > Running examples in package 'stats' > Error: testing 'stats' failed > Execution halted > make[3]: *** [test-Examples-Base] Error 1 Looking at R-2.9.2/tests/Examples/stats-Ex.Rout.fail I see: ... >

Hi, A. In a nutshell: The training error, obtained as "error (ret)", from the return value of a ksvm () call for a eps-svr model is (likely) being computed wrongly. "nu-svr" and "eps-bsvr" suffer from this as well. I am attaching three files: (1) ksvm.R from the the kernlab package, un-edited, (2) ksvm_eps-svr.txt: (for easier reading) containing only eps-svr

Hi all, I need some solution in the following problem. The following error appears when i use "mgcv" package for implementing GAM. But the same formula works fine in "gam" package. > model.gam <- gam(formula = RES ~ > CAT01+s(NUM01,5)+CAT02+CAT03+s(NUM02,5)+CAT04+ + CAT05+s(NUM03,5)+CAT06+CAT07+s(NUM04,5)+CAT08+s(NUM05,5)+CAT09+ +

Hi, I'm still trying to figure out that GLM procedure in SAS. Let's start with the simple example: PROC GLM; MODEL col1 col3 col5 col7 col9 col11 col13 col15 col17 col19 col21 col23 =/nouni; repeated roi 6, ord 2/nom mean; TITLE 'ABDERUS lat ACC 300-500'; That's the same setup that I had in my last email. I have three factors: facSubj,facCond and facRoi. I had this pretty

Hello, I want to plot several lines to a main plot but at the end of each loop, it erases the last one. Here my program: alpha<-5 beta<-10 var<-0.5 s<-runif(1000,0,50) m<-length(s) variancealpha<-0.002 variancebeta<-0.051 variancevar<-0.001 alphachap<-vector() betachap<-vector() varchap<-vector() epsilon<-vector() b<-vector()

Hi, I'm using R 2.12.0 on Windows XP. I've used the e1071 package to tune a Support Vector Regression object and I've created the SVR object: > epsilon.svr <- svm(C8R004 ~.,data = rain_flow.train, scale = T, type = "eps-regression", + kernel = "radial", cost = 0.9, epsilon=0.55,tolerance=0.001, shrinking=T, gamma=0.18,fitted=T) > esvr.pred <-

In my last e-mails, I have asked for help regarding 1. 'defining functions inside loops' 2. 'integrating functions / vector arithmetics' 3. 'vectors out of lists?' 4. 'numerical integration' Since some of these topics seemed to be relevant (I'm guessing by the # of replies I got), I'm posting a modified section of my code. Any thoughts on improvements would

I have a data with binary response variable, repcnd (pregnant or not) and one predictor continuous variable, svl (body size) as shown below. I did Hosmer-Lemeshow test as a goodness of fit (as suggested by a kind “R-helper” previously). To test whether the predictor (svl, or body size) has significant effect on predicting whether or not a female snake is pregnant, I used the differences between

Dears , I have the follow error when i want too use function abcnon of package bootstrap : Warning message: Package `bootstrap' contains no R code in: library(bootstrap) Can you help me ! Thx. AXA Corporate Solutions Nouveaux Produits Nour-Eddine HAKIM 52 Rue d'Amsterdame - 75009 Paris - France Tel (+33 1) 56 92 97 48 Fax (+33 1) 56 92 97 40 E-Mail : noureddine.hakim at

I couldn't resist: izeof(synth_buffs) = sizeof(float)*2*2*0x120 = 4 * 4 * 0x120 = 0x1200 = 4608 -Anish > -----Original Message----- > From: Segher Boessenkool [mailto:segher@chello.nl] > Sent: Monday, July 02, 2001 6:34 PM > To: vorbis-dev@xiph.org > Subject: Re: [vorbis-dev] ogg vorbis dynamic memory allocation. > > > > > Firelight Multimedia wrote: >

> From: Gamal Abdel-Azim [mailto:gamal at crinet.com] > > While trying to expand the memory/object size in R, I noticed > that R might be using > only heap memory. Is this true? Are all objects in R created > in the heap not > allocated? It's not logical that this is the case!! Otherwise > the whole R project would > be a total waste of time and resources.

I've managed to install CentOS 6 on a 192MB virtual machine using LiveCD install-to-disk graphical method. This is not normally possible because of: - hard-coded minimum supported memory in Anaconda installer - it will show a message "You do not have enough RAM to install CentOS Linux on this machine" if you try or force you to use seriously crippled text installer; - a bug in

Hello all, I'm in the process of moving over my Samba server (using LDAP). I believe everything is functioning correctly, except for this error I get when nmbd starts. Looking back at my old server, it was apparently doing this as well... so it may not even affect needed functionality. Still, I'd like to figure out why it's happening! If anyone has an idea, please let me

Hi, sorry if this is explained somewhere but I didn't find anything. How can I use "Anova" from the car package to test a modell without between subject's factors? Suppose I have the following data mat.1 mat.2 mat.3 di ex 1 85 85 88 1 1 2 90 92 93 1 1 3 97 97 94 1 1 4 80 82 83 1 1 5 91 92 91 1 1 6 83 83

Hi, I am trying to do run the following model saved in "C:/bugs/sus.bug" model { for (i in 1:n){ y[i] ~ dpois(lamdba[i]) log(lambda[i]) <- mu+bmale[male[i]]+bschn[schn[i]]+epsilon[i] # epsilon[i] ~ dnorm(0,tau.epsilon) } mu ~ dnorm(0,.0001) bmale ~ dnorm(0,.0001) tau.epsilon <- pow(sigma.epsilon, -2) sigma.epsilon ~ dunif(0,100) for (j in

I'm an experimental psychologist and when I run ANOVA analysis in SPSS, I normally ask for a test of non-sphericity (Box's M-test). I also ask for output of the corrections for non-sphericity, such as Greenhouse-Geisser and Huhn-Feldt. These tests and correction factors are commonly used in the journals for experimental and other psychology reports. I have been switching from SPSS to R

Dear List: I'm working to construct a very large sparse matrix and have found relief using the SparseM package. I have encountered an issue that is confusing to me and wonder if anyone may be able to suggest a smarter solution. The matrix I'm creating is a covariance matrix for a larger research problem that is subsequently used in a simulation. Below is the latex form of the matrix if