similar to: \examples{} in Rd file

Hi, everybody. I am working processing EEG data from 1000 pacients. I have a specific syntax to perform the Spectral Analysis and a loop to analyse all subjects. each subject data are in separate folders (P1, P2 P3...) My question is: in some cases, some errors can appear in one subject. I want to know if is possible to jump to the next subject and perform the same syntax , exibiting an error

Dear R-help list members, I have created a package 'mnormt' with facilities for the multivariate normal and t distributions. The core part is simply an interface to Fortran routines by Alan Genz for computing the integral of two densities over rectangular regions, using an adaptive integration method. Other R functions compute densities and generate random numbers. The starting

Hola! santes<-c(210,169,187,160,167,176,185,206,173,146,174,201,198,148,154) sdespues<-c(201,165,166,157,147,145,168,180,147,136,151,168,179,129,131) dantes<-c(130,122,124,104,112,101,121,124,115,102,98,119,106,107,100) ddespues<-c(125,121,121,106,101,85,98,105,103,98,90,98,110,103,82) presion<-data.frame( santes, sdespues, dantes, ddespues) logvero <-

Hi all, im triyng to implement a bayesian model with R and c++. I have a strange problem. I can't reproduce the error with a small script and then i post the original one. The problem is after the line for(MCMC_iter2=0;MCMC_iter2<thin;MCMC_iter2++) For the first 34 iterations all work fine, after, all the simulations of mu_acc_P return an "nan". If i delete the line

Dear R users, we are trying to do some parallel computing using library(snow). In particular we have a cluster with 3 nodes >cl <- makeCluster(3, type = "MPI") 3 slaves are spawned successfully. 0 failed. and we want to compute the function op_mat (see below) first with the master and then with the cluster using system.time for checking the computational performance.

Hi, I've estimated a simple kernel density of a univariate variable with density(), but after I would like to find out the CDF at specific values. How can I do it? thanks for your help, with it I am very close to finish my first little bit more serious work in R, Viktor

I have written the following function to calculate the weighted mean difference for univariate data (see http://www.xycoon.com/gini_mean_difference.htm for a related formula). Unsurprisingly, the function is slow (compared to sd or mad) for long vectors. I wonder if there's a way to make the function faster, short of creating an external C function. Thanks very much for your advice. gmd

There seems to exist peculiar cases where optim does not take care of constraints on the parameters to be optimized over. The call to optim is of the form opt <- optim(cp, fn=sn.dev, gr=sn.dev.gh, method="L-BFGS-B", lower=c(-Inf, 1e-10, -0.99527), upper=c( Inf, Inf, 0.99527), control=control, X=X, y=y, hessian=FALSE) The code has worked fine

In the document "R Data Import/Export", section "Output to connections", there is the following portion of code: ## convert decimal point to comma in output, using a pipe (Unix) zz <- pipe(paste("sed s/\\./,/ >", "outfile"), "w") cat(format(round(rnorm(100), 4)), sep = "\n", file = zz) close(zz) ## now look at the output

Dear All, I'm trying to use waldtest to test poolability (parameter stability) between two logistic regressions. Because I need to use robust standard errors (using sandwich), I cannot use anova. anova has no problems running the test, but waldtest does, indipendently of specifying vcov or not. waldtest does not appear to see that my models are nested. H0 in my case is the the vector of

Full_Name: Hao Yu Version: 1.4.1 OS: Windws and Linux Submission from: (NULL) (129.100.45.161) Hi, Recently we did some benchmarks regarding matrix inverse operation and found some strange things. See the following results (the package Matrix is most updated). 1. load the function Toeplitz and library(Matrix) "Toeplitz" function(x) { matrix(x[1 + abs(outer(seq(along = x),

Dear Spencer and Prof. Fox, Thank you for your replies. I'll very appreciate, if you have any ideas concerning the problem described below. First, I'd like to describe the model in brief. In general I consider a model with three equations. First one is for annual GRP growth - in general it looks like: 1) GRP growth per capita = G(investment, migration, initial GRP per

Caching computation in rails? Simple example: factorial modulus a large number input: integer x output: factorial( x ) % 12345678901234567 I want it so that if it computes factorial of N once, it will not have to compute for N again. code: class SiteController < ApplicationController caches_action :factorial, :inv def examine @inv = @params[''inv''] @outv =

Dear all, Paulo Ribeiro, p.ribeiro@lancaster.ac.uk, and myself noticed that R sometimes breaks down with a segmentation fault of (at least for us) unknown course. (We've read #411 and #671 in the bug report on "optim" -- the problem described there sounds familiar; but we have not found any hint on a segmentation fault.) Please find at the very end of this email the file

Hi, I want to do a meta-analysis with count data for treatement/control cases. Mi problem is that I need to use zero values (an informative zero value) for the mean and standard deviation for one of the treatement, but R has a problem: "Studies with zero values for sd.e or sd.c get no weight in meta-analysis". I can agroup the case by Family (byvar=Family). ¿Can you help me? Thanks!

Hi All, I *think* it's ddply because the function recognizes vr1, etc, in other parts of the function. Here's some code: # create dataset PROV.PM.FBCTS <- c(0.00 ,0.00, 33205.19, 25994.56, 23351.37, 26959.56 ,27632.58, 26076.24, 0.00, 0.00 , 6741.42, 18665.09 ,18129.59 ,21468.39 ,21294.60 ,22764.82, 26076.73) FBCTS.INV.TOT <- c(0 , 0, 958612, 487990, 413344, 573347,

I'm a week-old R user, and have become stuck trying to create usable CSV outputs for post-processing. I am using the package Rioja, which provides small datasets of results. I am running several analyses in a loop and iteratively adding the results to a *list* ("combined"). Within each iteration I use the following: > combined[[i]] <- performance(fit) With two iterations I

I have justed upgraded R v1.7.0 on Windows NT 4 and have installed the latest RMySQL (version 0.5-1)and DBI (version 0.1-5) packages. When I issue the following commands (tactfully adjusted) R just crashes and disappears, any ideas? require(RMySQL) m <- dbDriver("MySQL") con <- dbConnect(m, dbname="xxx", user="xxx", password="xxx",

Hi, there. Does anyone know the R function for calculating the cdf of bivariate normal distribution function? Thanks. Yulei [[alternative HTML version deleted]]

Since I have updated my Linux system, and consequently re-installed R, I am unable to see HTML documentation which I used to access via a web browser. To be more specific, my R installation is declared to be here: > R RHOME /usr/local/lib/R However, if I look at a location such as /usr/local/lib/R/library/base/html this contains only two entries File: 00Index.html File: R.css