similar to: R help for invoking nmmin()

Hi, I'm trying to get a toy program making use of nmmin to run successfully. I've gotten to the point of compiling. However, when I attempt to run my executable, I guess a bus error. I see that someone else has asked about using nmmin before <http://tolstoy.newcastle.edu.au/R/help/06/03/23944.html>, but I haven't come across any replies. Is there some documentation on how to

Hello, right now, i have a program to collect data into a table. right now, my table is table1 <- data.frame(trial = NA, x = NA, y = NA) for each time when i want to add data into my data, i have to copy data of table into an array for each column, and then i add new data into my array, then i copy my array into the table one column by one column. For example temptrial <- table1$trial;

Hi, I have read R's Writing Extensions manual and am still confused about how to use some of the routines there when I call from C. Specifically, I am writing a little test function which I will optimize using the nmmin function which underlies R's optim() with Nelder-Mead. I guess I wonder what library/header files I should be using. I was using R_ext/Applic.h and linking with libR but I

I would like to produce a complimentary log-log survival plot with only the points appearing on the graph. I am using the code below, taken from the plot.survfit page of help for the the survival package (version 2.35-7). I am running in R 2.10.0 on Windows XP, and the list of packages following the error is loaded. Is there some specific 'type= ' syntax, or an additional parameter that

Hi there I am new user of r, i would need some help to translate som code for vectors in matlab to r. I have managed to translate the first 7 rows, but not the rest. Could anyone give me any suggestions for this problem?? Matlab code: tempo=[]; temps=[]; tempn=[]; tempao=[]; tempas=[]; tempan=[]; for k=1:5 tempo = [tempo n_o(k,:)]; temps = [temps n_s(k,:)]; tempn = [tempn

I am trying to use the R API to call optim functions (nmmin, vmmin, lbfgsb, etc.) through a C program but I couldn't find the shared library to link under the R-2.6.0 build which is compiled under Linux (REL5). main.cpp:35: undefined reference to `Rf_initEmbeddedR(int, char**)' main.cpp:41: undefined reference to `nmmin' Thanks in advance for any help. ------------------------

Dear all, I have been trying to use R's optimization routines from C and I have some questions. Specifically, I am testing the usage of nmmin which performs Nelder-Mead optimization in order to learn how to do the above exercise. I understand from the notes in Chapter 5 that the declaration for both optimfn as well as nmmin are included in the header file R_ext/Applic.h so I have included

Sorry, that's a cut and paste error. It should be either tempx or xtemp throughout. Terry T On 06/11/2015 12:59 PM, John Nolan wrote: > Is there a misprint in your example? The first line of code uses tempx, but the rest uses a different variable xtemp? > > John > > -----"R-devel" <r-devel-bounces at r-project.org> wrote: ----- > To: "r-devel at

Dear list, I was trying to use the R API for optimization method "Simulated annealing" void samin(int n, double *x, double *Fmin, optimfn fn, int maxit, int tmax, double temp, int trace, void *ex); but I encountered the following problem: The implementation of the function samin (as seen in src/main/optim.c) passes its void * argument "ex" into the function

Hola. Estoy empezando a ver temas de series temporales y me gustaría saber como obtener con R los IVES (índices de variación estacionales). Por el momento estoy viendo cosas muy simples, como descomponer una serie en tendencia y componente estacional, usando la función decompose y también la función stl. Por ejemplo # generamos 48 datos de una normal por ejemplo x <- rnorm(48) # creamos el

A few weeks back I posted that the subset feature of rpart was not working when predicting a categorical variable. I was able to figure out a simple solution to the problem that I hope can be included in future editions of rpart. I also include a fix for another related problem. The basic problem is that when predicting a categorical using a subset, the subset may not have all the categories

(Apparently, I posted this to the wrong place. I am hopefully posting this is the correct place now. If not, please advise.) A few weeks back I posted that the subset feature of rpart was not working when predicting a categorical variable. I was able to figure out a simple solution to the problem that I hope can be included in future editions of rpart. I also include a fix for another related

Hi, I am trying to create what are called "spider diagrams" in the geochemical literature using R. A spider diagram is basically a plot of the atomic number versus the concentration on a log scale. Lines are drawn from each atomic number for each sample. Right now, my data frame looks like: SAMPLE SITE V3 LA.NASC LAATNUM CE.NASC CEATMNUM 1 1A:001

Dear Akshay, The best response was given by Andrew. "{...}" is not a closure. This is unusual for someone used to C-type languages. But I will try to explain some of the rationale. In the case that "{...}" was a closure, then external variables would need to be explicitly declared before the closure (in order to reuse those values): intermediate = c() { ??? intermediate

i want to estimate parameters with maximum likelihood method with contraints (contant numbers). for example sum(Ai)=0 and sum(Bi)=0 i have done it without the constraints but i realised that i have to use the contraints. Without constraints(just a part-not complete): skellamreg_LL=function(parameters,z,design) { n=length(z); mu=parameters[1]; H=parameters[2]; Apar=parameters[3:10];

The following code snippet taken from plot.survfit now gives me a surprising result: tempx <- c(0, 400, 0, 0) ytemp <- c(.0657, .98, 1, 0) plot(range(xtemp), range(ytemp), log='y', type='n') In that the max value for the x axis is now 10. The 0 on the end of ytemp was actually a mistake and shouldn't be there, if you remove it then the upper limit is sensible.

Hi all, I have a little problem. I make an weibull survival analysis using the survival package. It,s OK, them I have the functions. I plot this funcions with curve(). I want to make a plot with the real survival points (proportion of alive x time) and them add the curves to points. I have the time to dead, the censor data and my trataments. To analysis the model is: model1 <-

Hi everybody! I've a large dataset, about 2 Mio entries of the format which I would like to import into a frame: <integer><integer><float><string><float><string><string> Because to the huge data amount I've choosen a binary format instead of a text format when exporting from Matlab. My import function is attached below. It works fine for only

[Mod: Sent to linux-security instead of linux alert -- alex] Dave G. <daveg@ESCAPE.COM> wrote: > /* vixie crontab buffer overflow for RedHat Linux > * > * I dont think too many people know that redhat uses vixie crontab. > * I didn''t find this, just exploited it. The vulnerability involves an unguarded sscanf call in env.c. Enlarging the buffer to the largest

Platform T2000 SunOS ccluatdwunix1 5.10 Generic_125100-10 sun4v sparc SUNW,Sun-Fire-T200 I have a user that stated zfs is allocating more file system space than actually available via ls command versus what df -k shows. He stated he used the mkfile to verify if ZFS quota was working. He executes "ls -s" to report usage which reports more allocated than available from "df