similar to: Sending "..." to a C external

Full_Name: Glen Herrmannsfeldt Version: 2.2.1 OS: Linux Submission from: (NULL) (128.95.113.77) Following the discussion in "Writing R Extensions" in section 5.8.2, there is no indication that showArgs expects a pairlist() instead of a list(). I was trying .Call("showArgs",list(one=1,two=2,three=3)) for example, and getting many core dumps. It wasn't until reading

R developers, Last week I asked several questions which I think I can now answer myself in large part. > > Q 1) Is aov supposed to avoid qr decomposition and matrix inversion? > In S it is claimed to be faster than lm() for large datasets. Is > that due to avoidance of qr()? > (My main goal is to get the Error strata working.) My use of matrix

Full_Name: Guy W. Tillinghast Version: 2.8.0 OS: Windows XP professional Submission from: (NULL) (24.248.24.3) I am encountering difficulty asking R to manipulate the correct columns in Expression Set class (object 4). I download the ALL data with: library(golubEsets) data(Golub_Merge) Note, the data has the samples not in order. This is not R's fault (at least not that I can tell): >

Hi R users: I try this code, where "fun" is a parameter of a random generating function name, and I pretend to use "..." parameter to pass the parameters of different random generating functions. What am I doing wrong? f1<-function(nsim=20,n=10,fun=rnorm,...){ vp<-replicate(nsim,t.test(fun(n,...),fun(n,...))$p.value) return(vp) } This works! f1()

Hi, I'm updating the LMGene package from Bioconductor. "Writing R Extensions" suggests that all source files (the ones in the R directory) have a .R ending, so I added it to the (one) source file. The next time I installed and ran R, R didn't understand any of the functions. I tried various things and eventually went back to the file and dropped the .R ending, installed, ran R.

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Hi, I'm running some routines with standard matrix operations like solve() and diag(). When I do a profile, the lead item under total time is standardGeneric(). Furthermore, solve() and diag() have much greater total time than self time. ??? I assume there is some time-consuming decision going on in the usual functions; is there any way to avoid that and go straight to the calculaions? Thanks

I changed the path to include C:\Program Files\R\R-2.3.1\bin, but Rcmd check [package] just returns an error: 'Rcmd' is not recognized as an internal or external command, operable program or batch file. Any ideas? I want to be able to compile this package on Windows. [[alternative HTML version deleted]]

Hi, everyone! I have maybe very naive question, but nontheless. I'm experimenting with Kaleidoscope tutorial and I want to morph it into something similar to McCarthy's initial Lisp. For that, I need to implement symbols, which I thought I should implement as pointers to structures, and those structures would contain at least one field, which would be symbol's name. So, here's a

I'm solving the differential equation dy/dx = xy-1 with y(0) = sqrt(pi/2). This can be used in computing the tail of the normal distribution. (The actual solution is y(x) = exp(x^2/2) * Integral_x_inf {exp(-t^2/2) dt} = Integral_0_inf {exp (-xt - t^2/2) dt}. For large x, y ~ 1/x, starting around x~2.) I'm testing both lsoda and rk4 from the package odesolve. rk4 is accurate using step

This is a trivial example I set up to see if I could pass an environment and use the variables in it (this is for a function that will be called many times and might need to use a lot of variables that won't be changing, so it seemed more sensible to use an environment). Here's the code: ######################### #The outer function run.internal.env <- function(x) { in.env <-

Hi Lisp users, I'm a user of both Common Lisp and R (GNU R). I found R has a rich collection of statistical and numerical computation functions, while it is not as extensible as Lisp (Common Lisp). I considered Lisp-Stat but its only implementation is not in the usuall Common Lisp, and the available functions in CRAN are far richer than Lisp-Stat currently has. I want to know if there is

For some reason the mail didn't got through the first time, so sending it again. -------- Original Message -------- Subject: code-generating constant strings Date: Tue, 03 Dec 2013 01:56:11 +0100 From: Alexander Popolitov <popolit at gmail.com> To: llvmdev at cs.uiuc.edu. Hi, everyone! I have maybe very naive question, but nontheless. I'm experimenting with Kaleidoscope

I have written some programs in Common Lisp and I have been using SAS to pipe those programs to my lisp compiler in batch mode by using the %xlog and %xlst SAS commands. I wonder if there is in R a similar way to pipe commands to LISP so that all my work would be concentrated in R even when I have to call a LISP program? I have looked at the foreign library but this seems to adjust data types not

Scott Michel <scottm <at> rushg.aero.org> writes: > Out of curiousity, for which CL implementation is this targeted? sbcl? > Or something you're rolling? I wanted to roll out my own lisp, and maybe use some library code from existing lisps (think of loop or format). Adding an LLVM backend to an existing lisp implementation is a nice idea, but currently not planned. >

I mainly program in Common Lisp and use R for statistical analysis. While in R I miss the power and ease of use of Lisp, especially its many primitives such as find, member, cond, and (perhaps a bridge too far) loop. Has anyone created a package that includes R analogs to a subset of Lisp functions? Chris Elsaesser, PhD Principal Scientist, Machine Learning SPADAC Inc. 7921 Jones

Dear R-devel, There is a new feature in R-devel, which explicitly refers to LISP @ operator for splicing. > The backquote function bquote() has a new argument splice to enable splicing a computed list of values into an expression, like ,@ in LISP's backquote. Although the most upvoted SO question asking for exactly LISP's @ functionality in R doesn't seems to be addressed by this

R folks, I'm curious about possible support for Lisp-style macros in R. I'm aware of the "defmacro" support for S-Plus and R discussed here: http://www.biostat.wustl.edu/archives/html/s-news/2002-10/msg00064.html but that's really just a syntactic short-cut to the run-time use of substitute() and eval(), which you could manually put into a function yourself if you cared

I've read in many places that R semantics are based on Scheme semantics. As a long-time Lisp user and implementor, I've tried to make this more precise, and this is what I've found so far. I've excluded trivial things that aren't basic semantic issues: support for arbitrary-precision integers; subscripting; general style; etc. I would appreciate corrections or additions from

In porting some Common LISP code to R, I am trying to found out whether special care must be taken for the let* function. In Common LISP, "the let* block is like let except it is guaranteed to evaluate the initialization of its local variables in sequentially nested scopes, i.e. it provides an order to the binding and visibility of preceding variables.". I have included the recursive