similar to: Interesting remarks about R back in 1999

Dear R users, I was trying to install the package RXLisp by Duncan Temple Lang on a MDK 9.1 Linux machine running R 1.8.0 installed from a RPM. Unfortunately I had a problem loading the shared library into R. Since I'm a Linux newbie I was not able to solve the problem. Maybe some of you can help me. First of all I downloaded the source archive for Xlisp-Stat and for the RXlisp package.

I was obviously fascinated by Duncan's earlier message on RXLisp. I managed to build a working version of RXLisp for OS X, by some unabashed and rather uninformed hacking. I compiled XLISP-STAT using the gcc flags -fno-common and --no-cpp-precomp (not sure if they are necessary or not, they are part of an older hack). I "make libxlisp.so", using Duncan's replacement for the

Dear List: Is any one aware of a package that would extend the D() function and allow for one to maximize a likelihood function symbolically? Something akin to Solve[x==0, parameter] function in Mathematica? Clearly R has the capacity to _compute_ MLEs given a set of data. But, I'm looking for a package that would allow for me to define the likelihood function, find the 1st order partial

This may be a question to R-development but I'm not sure. Symbolic differentiation is implemented in R (maybe not for extremely complex expressions), but it proves that it can be done. I know that in C++ it can be done (symbolic c++), do you think in R it can be programmed just using the R language without resorting to external sources? Does anyone know or can estimate the amount of resources

I'm tinkering around in Ryacas trying to find an easy way to get the first and second partial derivatives of mu and sigma from a normal distribution (actually a bitterly ugly likelihood but this example works for now). I've done all of the work in Mathematica, but I then need to manually write R code whereas I think Ryacas will give me the expression such that I can export for Tex and

Hi, To my knowledge, Ryacas can do symbolic computation in R, like Mathematica or Maple. I wonder if it (or any other R package) can solve symbolically a system of equations? I have a system of four equations in four variables (non-linear, but not very hard to solve) and wonder if Ryacas or any other package can do it. I do not find the solution in Ryacas. Can it find a symbolic solution

Dear all, One of my friends asked me if it is possible to extract actual R function arguments literally (precisely, as strings). The reason is simple. He feels sometimes awkward to attach quotation marks :-). What he actually wants is to pass R command arguments to XLisp subroutines (He has been an enthusiastic XLisp user for a long time and still tends to use R as a wrapper to XLisp). Is it

Dear List: A while back I found a web site called the Rosetta Stone for Computer Algebra Systems showing how to do similar operations in different symbolic programs. This has been very helpful for moving between Mathematica, Yacas and Maxima. I wonder if anyone maintains something akin to this for translating R to SAS, Minitab, Stata etc? I am familiar with the various (useful) reference

There is either something wrong with either me or is Yacas/Ryacas doing odd things. See below I ask to simpify an expression and the there's output! If this is a simplification.. well.. Do you think there is something set wrong somewhere. Thanks. > library(Ryacas) Loading required package: XML > a=Sym("a") > N=Sym("N") > b=Sym("b") >

Dear all, I'm currently working on converting mathematica code (https://github.com/ASDSE/thermosimfit/blob/master/Packages/thermoHD-Comp/thermoCacheHD-1Comp.m) to R. The code is related to solve algebraic systems. > eqthermo = {h0 == h + hd + hga, d0 == d + hd, ga0 == ga + hga, kga == > ???? hga / (h * ga), kd == hd / (h * d)}; > > (* IDA HD*) > sthdIDAcacheHD[fkd_, fkga_,

Hello, I am trying to construct two matrices, F and V, composed of partial derivatives and then find the eigenvalues of F*Inverse(V). I have the following equations in ryacas notation: > library(Ryacas) > FIh <- Expr("betah*Sh*Iv") > FIv <- Expr("betav*Sv*Ih") > VIh <- Expr("(muh + gamma)*Ih") > VIv <- Expr("muv*Iv") I

What are some effective ways to leverage the strengths of R and Mathematica for the analysis of a single data set? More specifically, are there any functions that can assist with any of the following? 1. Calling an R function from Mathematica. 2. Calling a Mathematica function from R. 3. Using XML or another reliable data format to pass vectors, matrices, and/or lists from one environment to

Can someone help me understand the following: > D(expression(dnorm(x, mean)), "mean") [1] 0 > sessionInfo() R version 2.2.1, 2005-12-20, i386-pc-mingw32 attached base packages: [1] "methods" "stats" "graphics" "grDevices" "utils" "datasets" [7] "base" By my computations, this should be

Hi People, I have just started building my own RPMS on both Fedora and CentOS and generally things have gone well. Currently I am trying to create RPMS for some commercial software that we have purchased. Step 1 was install the software using its JAVA Based installer ensuring that all files were installed into a particular directory in /usr/local. Step 2 was create a tar file of the

Could anybody explain this results? >sin(2*pi) -2.449213e-16 #should be zero >(10^16)*sin(log2(4)*pi) -2.449213 #should be zero too and explain what to do to correct this events? Thanks!!! Branimir K. Hackenberger

Dear R-list members, I have a problem with translating a mathematica script into R. The whole script is at the end of the email (with initial values for easy reproduction) and can be pasted directly into R. The problematic part (which is included below of course) is <--- Original Mathematica ---> (* p_svbar *) UiA = Ni (Dsi - 2Di A + A^2)/2; UiiA = Nii (Dsii - 2Dii A + A^2)/2; psvbar =

I have some programs which were writen in mathematica or c language, but I donot know how to use these software. So I want to run them in R. Can I do it ? How to run "mathematica" or "c" programs in R? Jian Zhang [[alternative HTML version deleted]]

Full_Name: Skylab Gupta Version: R version 2.5.1 (2007-06-27) OS: Windows XP Submission from: (NULL) (216.82.144.137) Hello, I have been playing around with the statistical distributions in R. I think the computations for the cumulative distribution function of the students t distribution in R are not very accurate. For instance, the cdf of a students t distribution with 13 degrees of freedom

John Fox (see below) raises important questions for the Lisp-stat community (and perhaps the R community) to consider. This message thread was not cross-posted to r-devel@lists.r-project.org, so I do so now. I have never been an active or particularly adept Lisp-stat programmer. But I have worked on or used several projects for which Lisp-stat seemed the ideal environment-- for implementing

Hi all, I am an R newbie trying to do some calculations I do in Mathematica in R on a GNU/Linux system. The main thing I am interested in doing is taking a 0.999 quantile on a data set in a file who's data is normally distributed, say foo.csv. e.g in Mathematica if I have something like this : a=Import["foo.csv"] b=Transpose[a][[1]] Quantile[b,0.999] In R I can load all the data