search for: 0.149

I have pushed out klibc-0.149; the main difference is that I've done some serious work on the .spec file, and it should now be possible to just type "rpmbuild -ta klibc-####.tar.gz" and build an RPM that way. Still only includes the static binaries. Not 100% sure what the right thing there is. -hpa

Hi, I'm reading part of a table from postgres, so I'm getting a data frame. how can I extract the numerica values so I can operate on them. > res <- dbGetResult(mydata) > str(res) `data.frame': 5 obs. of 8 variables: $ cyx.1: num 0.149 -0.278 0.114 0.060 0.109 $ cyx.2: num 0.158 -0.070 0.063 0.149 0.150 $ cyx.3: num 0.052 -0.350 0.114 0.126 0.238

Hi r-users,   I would like to extract the data that match.  Attached is my data: I'm interested in matchind the value in column 'intg' with value in column 'rand_no' > cbind(z=z,intg=dd,rand_no = rr)             z  intg rand_no    [1,]  0.00 0.000   0.001    [2,]  0.01 0.000   0.002    [3,]  0.02 0.000   0.002    [4,]  0.03 0.000   0.003    [5,]  0.04 0.000   0.003    [6,] 

This command cdmoutcome<- glm(log(value)~factor(year) > +log(gdppcpppconst)+log(gdppcpppconstAII) > +log(co2eemisspc)+log(co2eemisspcAII) > +log(dist) > +fdiboth > +odapartnertohost > +corrupt > +log(infraindex) > +litrate > +africa >

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I have a table like the following. I want to fit Cm to Vm like this: Cm ~ Cl+Q1*b1*38.67*exp(-b1*(Vm-Vp1)*0.03867)/(1+exp(-b1*(Vm-Vp1)*0.03867))^2+Q2*b2*38.67*exp(-b2*(Vm-Vp2)*0.03867)/(1+exp(-b2*(Vm-Vp2)*0.03867))^2 I use nls, with start=list(Q1=2e-3, b1=1, Vp1=-25, Q2=3e-3, b2=1, Vp2=200). But I always get 'singlular gradient' error like this. But in SigmaPlot I can get the result. How

Full_Name: Sahotra Sarkar Version: 2.2.0 OS: Windows XP Professional Submission from: (NULL) (146.6.130.180) The following two commands should give the same results for the eigenvectors but do not (there is a sign reversal for the first one): > summary(princomp(bumpus),loading = TRUE) Importance of components: Comp.1 Comp.2 Comp.3 Comp.4 Comp.5

On 03/19/2013 11:02 AM, Star Tan wrote: > > Dear Tobias Grosser, > > Today I have rebuilt the LLVM-Polly in Release mode. The configuration of my own testing machine is: Intel Pentium Dual CPU T2390(1.86GHz) with 2GB DDR2 memory. > I evaluated the Polly using PolyBench and Mediabench. It takes too long time to evaluate the whole LLVM-testsuite, so I just choose the Mediabench from

Dear Tobias Grosser, Today I have rebuilt the LLVM-Polly in Release mode. The configuration of my own testing machine is: Intel Pentium Dual CPU T2390(1.86GHz) with 2GB DDR2 memory. I evaluated the Polly using PolyBench and Mediabench. It takes too long time to evaluate the whole LLVM-testsuite, so I just choose the Mediabench from LLVM-testsuite. The preliminary results of Polly compiling

Full_Name: Adrian Custer Version: 0.90.0 OS: Linux on Thinkpad (pentium) and desktop (K6) Submission from: (NULL) (128.32.251.234) When I create a boxplot, and then try to overlay a lowess fit or just the points, the points do not appear in the highest level and the lowess curve does not reach the highest level. However, if I add one to each of the models, the problem is solved. I tried this

Dear R gurus, I am interested in permutations-based cpu-intensive methods so I had to pay a little attention to Random Number Generators (RNG). For my needs, RNGs have to: 1) be fast. I profiled my algorithms, and for some the bottleneck was the RNG. 2) be scalable. Meaning that I want the RNG to remain fast as I add threads. 3) offer a long cycle length. Some basic generators have a

Hello R users, I am trying to calculate the stochastic lambda for a published matrix population model using the popbio package. Unfortunately, I have been unable to match the published results. Can anyone tell me whether this is due to slightly different methods being used, or have I gone wrong somewhere in my code? Could the answer be as simple as comparing deterministic lambdas to

Dear Tobias Grosser, Thank you so much for your kind reply. Your advice is very helpful and inspiring. At 2013-03-18 20:40:50,"Tobias Grosser" <tobias at grosser.es> wrote: >On 03/17/2013 11:54 PM, Star Tan wrote: >> Hello Tobi, >> >> I am interested in Polly project. Polly seems to be a very promising tool to find out program parallelization based on LLVM

Hi all I am trying to generate a normal unbalanced data to estimate the coefficients of LM, LMM, GLM, and GLMM and their standard errors. Also, I am trying to estimate the variance components and their standard errors. Further, I am trying to use the likelihood ratio test to test H0: sigma^2_b = 0 (random effects variance component), and the t-test to test H0:mu=0 (intercept of the model Yij = mu

Dear Tobies, Sorry for the late reply. I have checked the experiment and I found some of the data is mismatched because of incorrect manual copy and paste, so I have written a Shell script to automatically collect data. Newest data is listed in the attached file. Tobies, I have made a simple HTML page (attached polly-compiling-overhead.html) to show the experimental data and my plans for this

Dear R-help list, I would like to perform multiple comparisons for lme. Can you report to me if my way to is correct or not? Please, note that I am not nor a statistician nor a mathematician, so, some understandings are sometimes quite hard for me. According to the previous helps on the topic in R-help list May 2003 (please, see Torsten Hothorn advices) and books such as Venables &

Dear list, I am currently working with a rather large data set on body temperature regulation in wintering birds. My original model contains quite a few dependent variables, but I do not (of course) wish to keep them all in my final model. I've fitted the following model to the data: >

Dear R-help members, Apologies - I am posting on behalf of a colleague, who is a little puzzled as STATA and R seem to be yielding different survival estimates for the same dataset when treating a variable as ordinal. Ordered() is used to represent an ordinal variable) I understand that R's coxph (by default) uses the Efron approximation, whereas STATA uses (by default) the Breslow. but we

Hi group, I'm trying to do a Tukey test to compare the means of a factor ("treatment") with three levels in an lme model that also contains the factors "site" and "time": model = response ~ treatment * (site + time) When I enter this model in csimtest, it takes all but the main factor "treatment" as covariables, not as factors (see below). Is it

Dear List, I have been trying to use library sm to do density estimation on a 3D dataset. I am using the current MacOS X binary of sm from CRAN. If I do this on a 2D dataset, sm.density returns a list including the component "estimate" which contains the density estimate over a uniform grid. When doing this with 3D data, although I get a nice plot (even when I don't ask for one),