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Hi, here's a list of comments on python-theora: 1) http://certik.github.com/python-theora/module_theora.html#class-theora uses theora.test_files but setup.py does not install the test files so using this API fails with Traceback (most recent call last): File "browse-video.py", line 4, in <module> t = theora.Theora(theora.test_files[2]) File "theora.pyx",

Hi, We are looking for some guidance in installing an upgraded Python on our cluster. Our cluster was installed with Rocks 6.0, is running CentOs 6.2, and has python-2.6.6, gcc-4.4.6. We would like to install an upgraded version of Python along with the following modules NumPy Scipy (which will require a compatible version of the Atlas libraries) Mayavi (which will require a compatible

Hi all, While running the anscombe.test in R, I'm getting an error of *Error in if (pval > 1) pval <- 2 - pval : missing value where TRUE/FALSE needed* for a few time series columns whereas for most of the series the function is working fine. I have checked for those specific columns for missing values. However, there is no NA/NAN value in the dataset. I have also run kurtosis for

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Hi All, I found an interesting thread discussing R and other packages here: http://anyall.org/blog/2009/02/comparison-of-data-analysis-packages-r-matlab-scipy-excel-sas-spss-stata/ Plenty of well-reasoned comments. I thought it may be informative for people on this list. Best, - -Jose - -- Jose Quesada, PhD. Max Planck Institute, Center for

Folks: I'm trying to port some code from python over to R, and I'm running into a wall finding R code that can solve a generalized eigenvalue problem following this function model: http://docs.scipy.org/doc/scipy/reference/generated/scipy.linalg.eig.html Any ideas? I don't want to call python from within R for various reasons, I'd prefer a "native" R solution if one

HI, I've noticed what I think is an incorrect behavior of stats::psmirnov function and consequently of ks.test when run in an exact mode. For example: psmirnov(1, sizes=c(50, 50), z=1:100, two.sided = FALSE, lower.tail = F, exact=TRUE) produces 2.775558e-15 However, the exact value should be 1/combination(100, 50), which is 9.9e-30. While the absolute error is small, the relative error is

moments::anscombe.test(x) does give errors when x has too few values or if all the values in x are the same > moments::anscombe.test(c(1,2,6)) Error in if (pval > 1) pval <- 2 - pval : missing value where TRUE/FALSE needed > moments::anscombe.test(c(2,2,2,2,2,2,2,2)) Error in if (pval > 1) pval <- 2 - pval : missing value where TRUE/FALSE needed You can use tryCatch() to

Hi Bill, Thanks for prompt reply and letting me know a way around it. I have more than 1200 observations and not all the values are the same. However, my data points are quite similar, for example, 0.079275, 0.078867, 0.070716 in millions and etc. I have run the data without converting it to millions and I still get the same error message. As I have kurtosis value, it should be fine for the

I am using the non-linear least squares routine in "R" -- nls. I have a dataset where the nls routine outputs tight confidence intervals on the 2 parameters I am solving for. As a check on my results, I used the Python SciPy leastsq module on the same data set and it yields the same answer as "R" for the coefficients. However, what was somewhat surprising was the the

Another bad case is > moments::anscombe.test(rep(c(1,1.1),length=35)) Error in if (pval > 1) pval <- 2 - pval : missing value where TRUE/FALSE needed I haven't checked the formulas carefully, but I suspect the problem is from taking the cube root of a negative number in z <- (1 - 2/(9 * a) - ((1 - 2/a)/(1 + xx * sqrt(2/(a - 4))))^(1/3))/sqrt(2/(9 * a)) In R, the

Dear All Is there any software package like MATLAB for Windows available for centos? Thank you -------------- next part -------------- An HTML attachment was scrubbed... URL: <http://lists.centos.org/pipermail/centos/attachments/20100503/7a522211/attachment-0001.html>

Per the recent (seeming) consensus regarding incubating new projects under the LLVM organization, I would like to trial the process by requesting to incubate mlir-npcomp <https://github.com/google/mlir-npcomp>. The project is still quite young and has been primarily developed part time by myself and Sean Silva over the last ~2 months. We set it up following discussion of a Numpy/Scipy op set

Thanks for the response. I was not very clear in my original request. What I am asking is if in a non-linear estimation problem using nls(), as the condition number of the Hessian matrix becomes larger, will the t-values of one or more of the parameters being estimated in general become smaller in absolute value -- that is, are low t-values a sign of an ill-conditioned Hessian? Typical

I agree with many the sentiments about the wisdom of computing very small p-values (although the example below may win some kind of a prize: I've seen people talking about p-values of the order of 10^(-2000), but never 10^(-(10^8)) !). That said, there are a several tricks for getting more reasonable sums of very small probabilities. The first is to scale the p-values by dividing the

Dear R users, I would like to make my R code for MCMC faster. It is possible to integrate C code into R but I think C is too complicated for me. I would need a C introduction only for MCMC and I do not know if such a thing exists. I was thinking of Python (and scipy). Where could I read about its integration into R ? How developed are the statistical packages in Python ? I could not find a

Hola erreros Estoy rizando el rizo con esto de las matrices sparse y he encontrado la forma de hacerlo en python, que va rapidísimo. Por tanto tengo una matriz sparse en un objeto python con esta info: <138493x26744 sparse matrix of type '<type 'numpy.int64'> Quiero hacer lo mismo con R pero me he topado con la lentitud de los bucles para rellenar la sparse (también por mi

On 04/06/18 13:51, Ulf Volmer wrote: > On 06.04.2018 18:25, m.roth at 5-cent.us wrote: >> CentOS 7 box. As there's no package in any of the repos, we're trying to >> install scikit-learn in the user's space. It refuses. My late try was, >> after d/l a .whl from last year, hoping that would work with the numpy >> package in the regular repos, I did a pip

Hello, I don't know if this question ought to go here, or rather on R-devel, so please bear with me. I'm interfacing to R via RPy (rpy.sf.net) and an embedded Python interpreter. This is really quite convenient. I use this approach to calculate the correlation coefficient of 1 independent dataset (vector) with 4 dependent vectors. It'd be nice if that could be done in 4 parallel

Hello, I don't know if this question ought to go here, or rather on R-devel, so please bear with me. I'm interfacing to R via RPy (rpy.sf.net) and an embedded Python interpreter. This is really quite convenient. I use this approach to calculate the correlation coefficient of 1 independent dataset (vector) with 4 dependent vectors. It'd be nice if that could be done in 4 parallel

This thread reveals that R has some holes in the solution of some of the linear algebra problems that may arise. It looks like Jim Ramsay used a quick and dirty approach to the generalized eigenproblem by using B^(-1) %*% A, which is usually not too successful due to issues with condition of B and making a symmetric/Hermitian problem unsymmetric. In short, the problem is stated as follows: