similar to: Fit NLE - was: computer algebra in R

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_,

Dear Konrad, I presume that the system can be written as follows, where h0, d0, ga0, kga and kd are given: err1 = h + hd + hga - h0; err2 = d + hd - d0; err3 = ga + hga - ga0; err4 = hga - kga*h*ga; err5 = hd - kd*h*d; All error terms should be zero. Do you need (a) the symbolic solution or (b) is a numeric solution fine? I do not have any experience with yacas or caracas. But see below. ###

Dear R people Could you please help. Basically, there are two variables in my data set. Each patient ('id') may have one or more diseases ('diagnosis'). It looks like id diagnosis 1 ah 2 ah 2 ihd 2 im 3 ah 3 stroke 4 ah 4 ihd 4 angina 5 ihd .............. Q: How to make three data sets: 1. Patients with ah and ihd 2. Patients with ah but no ihd 3. Patients with ihd but no

Hello, I have a maybe trivial question, but I simply don't understand well enought how to work with text/strings: I have a rather compelx data structure, a big list with several sub-lists/dataframes and for certain calculations (which I do in loops), I only need a certain group of sub-lists/dataframes, which I want to specify with a name vector and paste together the object name and pass it

Dear R-users, I have some trouble to perform a 2-samples KS test. Apparently my 2 samples are numerical (see below) but R complains that the "y" term is not.... ------------------------------------------------------------------------------------- > str(subset(mydata,Identified=="NO",select=KD)) 'data.frame': 2889 obs. of 1 variable: $ KD: num -0.272 -0.080

Hello All, Thank you for taking my question. I am looking for information on how R handles interaction terms in a multiple regression using the ?lm? command. I originally noticed something was unusual when my R output did not match the output from JMP for an identical test run previously. Both programs give identical results for the main test and if the models do not contain the interaction

Dear list, Has anyone created a version of SSmicmen that allows testing for group differences? The basic Michaelis-Menten equation is: (Bmax * X) / (Kd + X). The nlme package allows modeling of random effects for Bmax and Kd as needed, but I curious how I can build in group differences? I have receptor binding data for strains of mice, and following Pinheiro and Bates' lead in their

Hi I hope this is going to the right place. I am trying to write a program which uses KernSmooth library to estimate mutual information between two time series at various different lags. At the moment it’s producing negative values, which is supposed to be impossible (something is fishy). I am summing across one row of the matrix to get p(value is in bin x) and summing across the columns to get

Hi, Sorry for my newbies questions... but here it is... My goal is to have a "shading language", it is very similar to the "C" language but with special tokens. I have a parser and a lexer done with Lex/bison, once I have lexed/parsed my "shading language" I must create 3 new "source code" in OpenCL. It mean that by example for the following : shader

Followup: I have checked my package nleqslv which uses dgemv only from Fortran, on Kubuntu 18.04 with the development version of R. No errors or problems. Berend > On 12 Sep 2019, at 08:57, Berend Hasselman <bhh at xs4all.nl> wrote: > > > I have tried what I proposed in a virtual Kubuntu 18.04 which uses gfortran 7.4. > I used the latest development version of R. >

Hello, I have been struggling with WinDbg/Kd for the last week, but to no avail... So I finally decided to ask here. Basically, I am using a Windows XP virtual machine (thanks to VMWare6) and wanted to do some kernel debugging using Windbg. So, I did configure everything from the virtual machine side (using this guide: http://silverstr.ufies.org/lotr0/windbg-vmware.html), and then tried my hands

Berend, I do not think this works with gfortran 7+. I am calling the BLAS subroutine dgemv from Fortran code in my package eha, and the check (with R-devel) gives: gmlfun.f:223:1: warning: type of ?dgemv? does not match original declaration [-Wlto-type-mismatch] & score, ione) ^ /home/gobr0002/R/src/R-devel/include/R_ext/BLAS.h:107:1: note: type mismatch in parameter 12

Hi all, I'm trying to do model reduction for logistic regression. I have 13 predictor (4 continuous variables and 9 binary variables). Using subject matter knowledge, I selected 4 important variables. Regarding the rest 9 variables, I tried to perform data reduction by principal component analysis (PCA). However, 8 of 9 variables were binary and only one continuous. I transformed the data by

On 2019-09-11 22:16, Avraham Adler wrote: > Can you write a small C function that calls LAPACK call that fro your > Fortran code? Yes, an extra step but maybe less traumatic than rewriting > parts of LAPACK directly. Yes, I know how to do that, but I find it somewhat bizarre that it is impossible to call a Fortran subroutine from Fortran. And rewriting 'dgemv' was simple:

I noticed a problem using R 2.7.1 on Windows XP SP2 with the precompiled Atlas Rblas.dll. Running the code below causes R to crash. I started R using Rgui --vanilla and am using the precompiled Atlas Rblas.dll from cran.fhcrc.org dated 17-Jul-2007 05:04 for Core2 Duo. The code that causes the crash: x <- rnorm(100) y <- rnorm(100) z <- rnorm(100) loess(z ~ x * y) loess(z ~ x) does

Hello R-helpers! I am trying to call a LAPACK subroutine directly from my R code using .Fortran(), but R cannot find the symbol name. How can I register/load the appropriate library? > ### AR(1) Precision matrix > n <- 4L > phi <- 0.64 > AB <- matrix(0, 2, n) > AB[1, ] <- c(1, rep(1 + phi^2, n-2), 1) > AB[2, -n] <- -phi > round(AB, 3) [,1] [,2] [,3]

Hello R-helpers! I am trying to call a LAPACK subroutine directly from my R code using .Fortran(), but R cannot find the symbol name. How can I register/load the appropriate library? > ### AR(1) Precision matrix > n <- 4L > phi <- 0.64 > AB <- matrix(0, 2, n) > AB[1, ] <- c(1, rep(1 + phi^2, n-2), 1) > AB[2, -n] <- -phi > round(AB, 3) [,1] [,2] [,3]

Hi, I am segfaulting when using predict.loess() (checked with r62092). I've traced the source with the help of valgrind (output pasted below) and it appears that this is due to int overflow when allocating an int work array in loess_workspace(): liv = 50 + ((int)pow((double)2, (double)D) + 4) * nvmax + 2 * N; where liv is an (global) int. For D=1 (one x variable), this overflows at

Hello everyone, I have biological data from a competition experiment where a free ligand is titrated against the binding of a protein. Now, I would like to fit a standard on-site binding curve to this data in order to obtain the IC50 and Kd values. Unfortunately I have not been able to find a package/function which allows such a fitting and calculates the results. Does anyone know if there is

Good morning! I recently implemented a KD tree in JAVA for faster kernel density estimation (part of the code follows). It went well. To hook it with R, however, has proved more difficult. My question is: is it possible to implement the algorithm in R? My impression seems to indicate no as the code requires a complete class-object framework that R does not support. But is there an R package or