similar to: separate y-limits in xYplot panels

Hello! I downloaded a package "multtest" (from bioconductor.org) in R, and installed it by 'R CMD <package>' (after unzipping and taring). The problem is when I say 'library(multtest)' in R, the following error is generated: Error in dyn.load(x, as.logical(local), as.logical(now)) : unable to load shared library

I have a lattice plot that has 4 pages with 4 columns and 8 rows per page. I wish to have the rows use a separate x-axis since their ranges are quite different, but I wish to have those same limits used on each page. By setting an element of the scales list to something like x = list(limits = lim.list$CFU, lim.list$CFU, lim.list$CFU, lim.list$CFU,

Dear List, I am looking for a function `Pseudo standard error' (PSE), which is available in S+ DOX (design of experiemnt) module - Is there a similar function available in R? Reference for PSE function is in the paper: 'Quick and easy analysis of unreplicated factorials' by Russell V. Lenth, Technometrics, 1989, 31, 4, 469-473. Thanks. -Nitin

Hello, I am building a R-package for Genetics analysis. The accepted data is in pedigree (.ped) file format. To load the data (say CAMP.ped) from "data" directory, I have a function "CAMP.R", which does the job. The package builds successfully in Linux (.tar.gz) and the data loads successfully by "data(CAMP)". However, when I build the package in WINDOWS, the data

Hi, I've stumbled upon a case where I think gvn does a bad (wrong) optimization. It's a bit messy to debug though so I'm not sure if I should just write a PR about it a let someone who knows the code look at it instead. Anyway, for the bug to trigger I need to run the following passes in the same opt invocation: -sroa -instcombine -simplifycfg -instcombine -gvn The problem

Dear R-devel members, We are building a new package (GeneticsBase) for analysis of genetic data . While doing "R CMD check with R-2.1.1, I am getting the following error: ** building package indices ... Error in "colnames<-"(`*tmp*`, value = c("family", "pid", "father", "mother", : length of 'dimnames' [2] not equal to

Hi. I am trying to use the linear optimizer from package lpSolve in R 2.4.1 on Windows XP (Version 5.1). The problem I am trying to solve has 2843 variables (2841 integer, 2 continuous) and 8524 constraints, and I have 2 Gb of memory. After I load the input data into R, I have at most 1.5 Gb of memory available. If I start the lp with significantly less memory available (say 1 Gb), I get

Hi all, I realize this is asking a lot of lattice, but I want to add a second y axis inside a xyplot and have y1 and y2 have different ranges. Given dat below, I can add a second y axis by overlaying a new plot with par(new=T) and label axis 4 with standard graphics. I've seen an example for doing something similar in xyplot even though Deepayan has indicated that lattice isn't the right

Hello, I have a dataset with a continuous independent variable (fish length, range: 30-150 mm) and a binary response (foraging success, 0 or 1). I want to discretize fish length into 5 mm bins and give the proportion of individuals who successfully foraged in each each size bin. I have used the cut function to discretize the length values into my desired bins, but I can't figure out how to

I am using metafor to create forest plots. This code gives me the expected plot (setting x axis tick marks): forest(forest$OR, ci.lb=forest$Low, ci.ub=forest$High, at=log(c(.05, .25, 1, 10)), slab=forest$SNP, atransf=exp) As does this (setting colors): forest(forest$OR, ci.lb=forest$Low, ci.ub=forest$High, col=c(1,2,3), slab=forest$SNP, atransf=exp) But if I try to set both 'at' and

Hello, I am performing a meta-analysis using the metafor package. My data are proportions and I used the Freeman Tukey double arcine (FT) transformation to fit the random effects model. Now I want to create a forest plot with my estimates backtransformed to the original scale of proportions. Can this be done? Regards, Patricia

Full_Name: Cesar Henrique Torres Version: 2.2.0 OS: winXP-pro Submission from: (NULL) (201.1.196.50) Hi developer's! I'd like to know were gtools package is, because in the link below it isn't: http://cran.r-project.org/bin/windows/contrib/r-release/ This package is used in gplots and I'm trying to make a balloonplot. Thanks a lot, Cesar Torres.

Yeah, there's a lot of things this could be. On the memdep side: Note that memdep is not actually properly updated in all cases by most passes that claim to not invalidate it (they don't invalidate dependent pointers, only pointers they directly touch). There's already a bug filed about this. So far we've only seen missed-opt, not wrong code from this. But it should be possible

Estimados, tengo un grafico al que debo anexar la leyenda en el costado derecho. Mi problema es que el titulo de la leyenda debe decir "Concentration (mM)" el que es muy largo y la ultima M sale cortada. No puedo abreviar la palabra porque justamente me rechazaron el grafico por que estaba abreviada esa palabra. Aqui pego el codigo con el que se hacen los graficos y anexo un archivo

Dear R-users I need to calibrate kappa, rho, eta, theta, v0 in the following code, see below. However when I run it, I get: y <- function(kappahat, rhohat, etahat, thetahat, v0hat) {sum(difference(k, t, S0, X, r, implvol, q, kappahat, rhohat, etahat, thetahat, v0hat)^2)} > nlminb(start=list(kappa, rho, eta, theta, v0), objective = y, lower =lb, > upper =ub) Error in dots[[1L]][[1L]] :

Tom Cohen <tom.cohen78@yahoo.se> skrev: Thanks Prof Brian for your suggestion. I should know that for right-skewed data, one should generate the samples from a lognormal. My problem is that x and y are two instruments that were thought to be measured the same thing but somehow show a wide confidence interval of the difference between the two intruments.This may be true that these

Hello, Is it possible to have two meta-plots in one graph (not par(mfrow=c(2,1))? But somthing like  library(metafor)  library("igraph")    if (interactive()) {     forest(dat.Treat$RR, ci.lb=dat.Treat$lower, ci.ub=dat.Treat$upper, xlab="Relative Risk",slab=dat.Treat$ID,refline=1)     forest(dat.Control$RR, ci.lb=dat.Control$lower, ci.ub=dat.Control$upper, xlab="Relative

Hi everyone, i?m a new user of R and i?m trying to translate an linear optimization problem from Matlab into r. The matlab code is as follow: options = optimset('Diagnostics','on'); [x fval exitflag] = linprog(f,A,b,Aeq,beq,lb,ub,[],options); exitflag fval x=round(x); Where: f = Linear objective function vector (vector of 45,rows) A = Matrix for linear inequality

I generate random vector from Weibull distribution sampWB <-urweibull(sampleSize, shape=shape.true, scale=scale.true, lb=0, ub=Inf) how can I create subvector containing 30% of samplesize of sampWB which should be assigned as Censored data? The probability for each value in sampWB can be uniform to be included in the subvector.

Dear all, I am a new user to R and I am using pracma and nloptr libraries to minimize a numerical integration subject to a single constraint . The integrand itself is somehow a complicated function of x and y that is computed through several steps. i formulated the integrand in a separate function called f which is a function of x &y. I want to find the optimal value of x such that the