similar to: R-beta: "Comparison of Mathematical Programs for Analysis"

Hello everybody, I am making a modified version of "Stephan Steinhaus' benchmark test for number crunching, v. 2, (see http://www.scinetificweb.com/ncrunch/ncrunch.pdf for the original version), comparing several functions of some math/stat software. R is not performing bad at all... except for the sorting of a 1,100,000 random vector (test #3) which is the worst of all (see cell F3 in

Hello everybody, I am making a modified version of "Stephan Steinhaus' benchmark test for number crunching, v. 2, (see http://www.scinetificweb.com/ncrunch/ncrunch.pdf for the original version), comparing several functions of some math/stat software. R is not performing bad at all... except for the sorting of a 1,100,000 random vector (test #3) which is the worst of all (see cell F3 in

Hi All, I've just rebuild the latest R with the Goto BLAS on our new Intel quad core machines. I did a few basic matrix calculations, and I was very impressed by the performance I saw. I wonder if anyone has a more rigorous benchmarking program for R. I downloaded a old R test/benchmarking program (see below), and this didn't work with the current R, and so I wondered if anyone could

All: I have a matrix, X, with a LARGE number of rows. Consider the following three rows of that matrix: 1 1 1 1 2 2 3 3 1 1 1 1 3 3 2 2 3 3 2 2 1 1 1 1 I wish to fit many one-way ANOVAs to some response variable using each row as a set of factors. For example, for each row above I will do something like anova(lm(Y~as.factor(X[1,]))). My problem is that in the above example, I do not want

hi there, trying to follow the steps of Yan & Rossini 2003, I have two problems : first when I 'make CrossCompileBuild', I get : ****************************************************************************** make[1]: Entering directory `/home/ros/RWORK/CROSSSOMP/WinR/R-1.8.0/src/gnuwin32' make -f Makefile.docfiles make[2]: Entering directory

Intrinsics can return `llvm_any_ty` (Intrinsics.td). In that case the return type is added as a suffix to the intrinsic's name, i.e. the syntax in the RFC is not 100% the syntax for intrinsics. Same for the parameters which each must have their types explicitly mentioned. Michael Am Mo., 22. Juli 2019 um 19:08 Uhr schrieb Kaylor, Andrew <andrew.kaylor at intel.com>: > > Is it

All: I am trying to use gam in a scatterplot smoothing problem. The data being smoothed have greater 1000 observation and have multiple "humps". I can smooth the data fine using a function something like: out <- ksmooth(x,y,"normal",bandwidth=0.25) plot(x,out$y,type="l") The problem is when I try to fit the same data using gam out <-

It's also very common in Fortran. -David Michael Ferguson via llvm-dev <llvm-dev at lists.llvm.org> writes: >> It seems that the main advantage of your proposal is that it would >> allow for non-constant strides (i.e. variable length arrays) in >> dimensions other than the first one. Do these appear frequently >> enough in the programs

We could also simply extend the existing inrange mechanism to non-constantexpr GEPs.  It would remove an inconsistency in the semantics, be relatively straight forward, and solve the motivating example. (I didn't read the proposal in full, so there may be other examples it doesn't solve.) Philip On 7/22/19 10:01 AM, Peter Collingbourne via llvm-dev wrote: > The restrictions of

Sorry: I should have reproduced the "problem" with a simple example. I do this below. I think there is likely a switch I can change using par, but don't know what it is. The problem is the tick marks for the Y- axis are only on plots in column #1 and for the X-axis in row # 2. Tony x <- 1:10 y <- 1:10*5 par(mfrow=c(2,2)) plot(x,y) plot(x,y) plot(x,y) plot(x,y)

> It seems that the main advantage of your proposal is that it would allow for non-constant strides (i.e. variable length arrays) in dimensions other than the first one. Do these appear frequently enough in the programs that you're interested in to be worth optimizing for? Yes - at least in Chapel (which is one of the motivating languages) these are very common. In other words, typical

Hi, Is there any R library that is capable of handling polygamma function (Hurwitz zeta function also works)? I am aware of digamma(0 and trigamma(), but could not find more advanced versions. I'd appreciate any help. Hakan Demirtas

Hello, We would like to begin discussions around a new set of intrinsics, to better express multi-dimensional array indexing within LLVM. The motivations and a possible design are sketched out below. Rendered RFC link here <https://github.com/bollu/llvm-multidim-array-indexing-proposal/blob/master/RFC.md> Raw markdown: # Introducing a new multidimensional array indexing intrinsic ## The

Hi, I think I understand what the problem is. The return type will also be an untyped pointer, just like GEP. However, GEP needs to know what the size of one element is. Like it is now with overloadable intrinsics, we might derive it from the suffix. Another solution is that we pass the element and array sizes in bytes, instead of multiples of the element size. As a third options, we might change

I am trying to use dynamic loading of an outside C routine. I am attempting 6.12.1 of Phil Spector's book. When I try to load the object file I get an error I don't understand: > dyn.load("runa.o") Error in dyn.load(x) : unable to load shared library "/usr/home/tdlong/run_avg/runa.o": /usr/home/tdlong/run_avg/runa.o: ELF file's phentsize not the expected

All: Are there any functions out there for selecting all the points in a region of a plot. I envision something like the identify() function except one could circle a cloud of points (and perhaps a vector would be returned of the same length as the points plotted indicating logical membership in the circled cloud). Perhaps someone has done something with the locator() function that would

I am running R version ??? under Redhat 5.2. It seems as though the --nsize object has no effct on the size of the allocated Ncells as determined using gc(). Yes, I have that much data.... That is if I envoke R with R --vsize 100 --nsize 5000000 then type gc() I get free total Ncells 92202 200000 Vcells 12928414 13107200 Thanks Tony Long Ecology and Evolutionary Biology Steinhaus

All: I am getting an error code from the optimization function. The code is Error in optim(p,fun.LLike, lower=low, upper = up, method = "L-BFGS-B", : non-finite finite-difference value [0] If I add a trace=6 option to my control list the last message before this error is: At X0, 0 variables are exactly at the bounds Any ideas on where I should start would be

Hello, I am writting a program in C++ and I need to use the function polygamma. I wonder if I can call this function that is included in the R library from my program in C++. Thanks a million, Isabel

Dear R Core Team, I am using package {urca} to do cointegration and estimate ECM model, but I have the following two problems: (1) I use ca.jo() to do cointegration first and can get the cointegration rank, alpha and beta. The next step is to test some restrictions on beta with blrtest(),bh5lrtest(), and bh6lrtest(). But none of them can add restrictions on all the cointegration