similar to: loops & sampling

---------- Forwarded Message ---------- Subject: Re: [R] conditional coloring of image labels Date: Friday 11 November 2005 1:04 pm From: jim holtman <jholtman at gmail.com> To: Jake Michaelson <jjmichael at cc.usu.edu> Use 'mtext': genes=cbind(ABC1=c(3,4,4,5,6,3), ABC2=c(4,3,4,7,7,8), ABC3=c(8,7,8,6,3,2)) ###plot the image image(1:nrow(genes), 1:ncol(genes), genes, axes =

Hi all, I am interested in plotting a heatmap of a set of genes. I would like the text labels of these genes to be colored red rather than black if they meet certain statistical criteria (using an if statement). I'm not sure how to change individual color labels without changing them all. Can anyone provide some insight on how to do this? Thanks in advance, Jake

Hi, I am new to clustering and was wondering why pvclust using "maximum" as distance measure nearly always results in p-values above 95%. I wrote an example programme which demonstrates this effect. I uploaded a PDF showing the results Here is the code which produces the PDF file: ------------------------------------------------------------------------------------- s <-

Hi, maybe someone can help me with this: I have a matrix of genes and values: GeneName Value Abc1 10 Abc2 11 Bbc1 -5 Bbc31 2 Ccd 5 Ccd -2 Ccd 7 Dda 5 Dda 10 ..... ..... Zzz3 -1 I would like to

Hi,I am currently doing a project in which we are to investigate the size and power of three different one sample tests over three different distributions using a number of different sample sizes and values for mu1. I have written a function and was trying to get my answer for each test into the right position in an array so the output is the power of each combination of test, distribution, sample

I wonder if someone could help me adjusting the following code to parallelized snow code: #Creating a data set (not needed to be parallel) n<-100 p<-100 x<-matrix(rnorm(n*p),p) y<-rnorm(n) # Bootstrapping nboot<-1000 alpha<-0.05 rhoboot <- array(0, dim=c(p,nboot)) bootranks <- array(0, dim=c(p,nboot)) bootsamples <- array( floor(runif(n*nboot)*n+1), dim=c(n,nboot)) for

Hi, how can I change a defined factor-variable? Like adding levels, renaming existing levels or merge several levels of a factor to one level? For example; following factor-variable is given: x <- factor(c("xyz1", "abc1", "xyz2", "abc2")) How can I add the level fgh? And how can I merge "xyz1" and "xyz2" to one level? And

Hello, If you want to bootstrap a statistic, I suggest you use base package boot. You would need the data in a data.frame, see how you could do it. library(boot) bootMedianSE <- function(data, indices){ d <- data[indices, ] fit <- rq(crp ~ bmi + glucose, tau = 0.5, data = d) ypred <- predict(fit) y <- d$crp median(y - ypred)^2 } dat <-

Dear R-experts, I am trying to bootstrap (and average) the median squared error evaluation metric for a robust regression. I can't get it. What is going wrong ? Here is the reproducible example. ############################# install.packages( "quantreg" ) library(quantreg) crp <-c(12,14,13,24,25,34,45,56,25,34,47,44,35,24,53,44,55,46,36,67) bmi

Hello, &nbsp; I want to sum first three terms of each column of matrix. But I don't calculate with "apply" function. &nbsp; skwkrt&lt;-function(N=10000,mu=0,sigma=1,n=100, nboot=1000,alpha=0.05){ x&lt;-rnorm(N,mu,sigma)#population samplex&lt;-matrix(sample(x,n*nboot,replace=T),nrow=nboot) #... } &nbsp; is that: suppose a is a 5x2 matrix. &nbsp;a={1,2,3,4,5

Hello all, I am re-posting my previous question with a simpler, more transparent, commented code. I have been ramming my head against this problem, and I wondered if anyone could lend a hand. I want to make parallel a bootstrap of a linear mixed model on my 8-core mac. Below is the process that I want to make parallel (namely, the boot.out<-boot(dat.res,boot.fun, R = nboot) command).

Hello, My question likely got buried so I am reposting it in the hopes that someone has an answer. I have thought more about the question and modified my question. I hope tha my specific question is: I am attempting to create a bootstrap procedure for a finite sample using the theory of Rao and Wu, JASA (1988) that replicates within each strata (h) n_h - 1 times. To this end, I require a

Hi all, I have a problem with getting my code to do what I want! This is the code I have: create.means.one.size<-function(nsample,var,nboot){ mat.x<-matrix(0,nrow=nboot,ncol=nsample) for(i in 1:nboot){ mat.x[i,]<-sample(var,nsample,replace=T) } mean.mat<-rep(0,nboot) for(i in 1:nboot){ mean.mat[i]<-mean(mat.x[i,]) } sd.mean<-sd(mean.mat) return(mean.mat) } where

Hi, I am using errorest function from ipred package. I am hoping to perform "bootstrap 0.632+" and "bootstrap leave one out". According to the manual page for errorest, i use the following command: ce632[i]<-errorest(ytrain ~., data=mydata, model=lda, estimator=c("boot","632plus"), predict=mypredict.lda)$error It didn't work. I then tried the

Hi together, after I read "very often" without even a tiny bit of a contradiction, I start to have the feeling I have a basic misunderstanding of rsync. Assume one want to get a list of files which would have been transfered by rsync if rsync was requested to sync directories X and Y and one does <code> X=`mktemp` echo "abc" > $X/1 echo "abc1" > $X/2

Hi all, I am using samba 3.5.8 on a linux machine. I am not able to join the domain of a windows 2003 server in ADS mode. I am getting the following error message: # /usr/local/samba/bin/net ads join -U Administrator%password -I 10.25.66.71 Failed to join domain: failed to find DC for domain ABCDOM.PQR.COM # I am not sure what the issue here. It works absolutely fine when I try to join the

Hallo everybody! I am trying to perform a TiTAN (Baker & King 2010) analysis with R 2.14.1. I have come that far: h89Abund <- read.csv("Fish89Abund.csv") > names (Fish89Abund) [1] "StationCode" "Abramisbrama" "Alburnoidesbipunctatus" "Alburnusalburnus" [5] "Ameiurusmelas" >

Hola, Quiero especificar una ecuación con varias variables explicativas de una manera eficiente sin necesidad de escribir todas y cada una. Tengo un conjunto de variables (junto con otras) dentro de una base de datos que se llaman pot23 pot311 pot312 pot 316 pot317........... pot80. No necesariamente están secuenciadas. Quisiera saber cómo indicar que incluya todas las variables de pot23 a pot80

Hola: tengo un pequeño problemita que es más bien estadístico que específico de R, pero de todos modos espero me puedan dar una mano. Quiero encontrar una forma de reportar la Bondad de ajuste de un modelo No Lineal. Estuve buscando y leyendo y parece que tal cosa no es posible o al menos no es fiable, desde el punto de vista estadístico. El tema es que quiero mandar un trabajo a una

Hello, I'm with a conceptual doubt regarding Rsquared of both lm() and postResample(library caret). I've got a multiple regression linear model (lets say mlr) with anR² value of 67.52%. Then I use this model pro make predictions with predict() function using the same data as input , that is, use the generated model to predict the value associated with data that I used as input. Next, if