search for: tim_smith_666

Hi, I was trying to get hyperlinks using xtable, but couldn't get the hyperlinks to function properly. For example, if I use ## Try to link NY times website to every figure in column 4 mat <- matrix(1:43,6,5) mat[,5] <- "http://nytimes.com" for(i in 1:nrow(mat)){ strr <- paste('<a href="', mat[i,5],'">', mat[i,4], '</a>',

Hi, I was trying to get a graph in lattice with the following data frame (7 rows, 5 cols): chr start1 end1 meth positive 1 1 10 20 1.5 y 2 2 12 18 -0.7 n 3 3 22 34 2.0 y 4 1 35 70 3.0 y 5 1 120 140 -1.3 n 6 1 180 190 0.2 y 7 2 220 300 0.4 y I wanted the panels to be organized by 'chr' -

Hi, I was trying to read in a file test.txt, which has the following data: norm norm norm class class class a 1 2 3 4 5 6 b 3 4 5 6 7 8 c 5 6 7 8 9 10 in my R code, I do the following: --------------------------------------------------- > mat <- read.table('test.txt',header=T,row.names=1,sep='\t') > mat norm norm.1 norm.2 class class.1 class.2 a 1 2 3

Hi, Is there a way I can draw an abline on a heatmap? I try the abline function, but don't get the line. My sample code is: mat <- matrix(sample(1:100,40),nrow=5) heatmap(mat,col=greenred(75),trace="none", dendrogram = "column",labCol = NULL) abline(h=5,v=4) thanks! [[alternative HTML version deleted]]

Hi, I was looking for a package that would help with outlier detection for bimodal distributions. I have tried 'outliers' and 'extremevalues' packages, but am not sure if they are ok for bimodal distribution. Any help would be highly appreciated! thanks, [[alternative HTML version deleted]]

Hi, I had a function that looked like: diff <- lm(x ~ y + z) How can I pass the argument to the 'lm' function on the fly? E.g., if I pass it in as a string (e.g. "x ~ y + z"), then the lm function treats it as a string and not a proper argument. many thanks [[alternative HTML version deleted]]

Hi, I must be missing something here...Essentially, a short piece of code works if it's standalone, but doesn't work if it's divided into two functions. The code that works is: ################### WORKS ############### library(pamr) set.seed(120) x <- matrix(rnorm(1000*20),ncol=20) y <- sample(c(1:4),size=20,replace=TRUE) mydata <- list(x=x,y=y)

Hi All, This is probably a very simple question. I was trying to add a row to the rows in a matrix. For example: > a <- matrix(1:6,2,3) > > b <- a[1,] > > print(a) [,1] [,2] [,3] [1,] 1 3 5 [2,] 2 4 6 > > print(b) [1] 1 3 5 I now want to add 'b' to every row of 'a', so the end result should look like: [,1]

Hi, I was trying to overlay/combine two freqpoly plots. The sample code below illustrates the problem. Essentially, I want to do is: 1. Have the same colour for all the lines in 'Plot 1' (and 'Plot 2'). Currently, all the lines in Plot 1 have different colours and all the lines in Plot 2 have different colors. I'd like for all lines in Plot 1 to be 'red' and all

Hi, I wanted to install the gWidgets package and ran the following code: ------------------------------------------ > install.packages("gWidgets") trying URL 'http://www.ibiblio.org/pub/languages/R/CRAN/bin/windows/contrib/2.7/gWidgets_0.0-30.zip' Content type 'application/zip' length 1354268 bytes (1.3 Mb) opened URL downloaded 1.3 Mb package 'gWidgets'

Hi, I wanted to plot 2 lines on a single graph. Each graph has one axis that can be common. The code that I'm using is: ------------------------------------------------------- par(mfrow=c(1, 1)) x1 <- c(2, 4, 6, 8, 10, 12) x2 <- c(10, 20, 30, 40, 50, 60) y1 <- c(10,12,15,22,34,21) y2 <- c(40, 130, 150, 145, 40, 30) par(las=1, mar=c(4, 4, 2, 4)) plot.new()

Hi, I was trying to make another legend for the rug plot. Sample code: library(ggplo2) ids <- paste('id_',1:3,sep='') before <- sample(9) after <- sample(1:10,9) dat <- as.matrix(cbind(before,after)) rownames(dat) <- rep(ids,3) position <- c(rep(10,3),rep(13,3),rep(19,3)) mdat <- cbind(melt(dat),position) ggplot(mdat, aes(position, value)) +

Hi, I was working on a classification problem using the pamr package. I used the pamr.adaptthresh() function to find the optimal accuracy of the classifier. I must not be doing it right, since it doesn't return the threshold values for optimum classification. For example,if I run it on a dataset, I get the following result using pamr.adaptthresh(): predicted true (1)

Hi, I was working on a classification problem using the pamr package. I used the pamr.adaptthresh() function to find the optimal accuracy of the classifier. I must not be doing it right, since it doesn't return the threshold values for optimum classification. For example,if I run it on a dataset, I get the following result using pamr.adaptthresh(): predicted true

Hi, Sorry about the earlier formatting errors... I was working on a classification problem using the pamr package. I used the pamr.adaptthresh() function to find the optimal accuracy of the classifier. I must not be doing it right, since it doesn't return the threshold values for optimum classification. For example,if I run it on a dataset, I get the following result using

Hi, I was trying to get the optimal 'k' for the knn. To do this I was using the following function : knn.cvk <- function(datmat, cl, k = 2:9) { datmatT <- (datmat) cv.err <- cl.pred <- c() for (i in k) { newpre <- as.vector(knn.cv(datmatT, cl, k = i)) cl.pred <- cbind(cl.pred, newpre) cv.err <- c(cv.err, sum(cl != newpre)) }

Hi, Is there any package that implements semi-supervised clustering through 'must-link' and 'cannot-link' constraints? thanks! __________________________________________________ [[alternative HTML version deleted]]

Hi, Is there any clustering package in R that can cluster with ordinal data? thanks! ____________________________________________________________________________________ Be a better friend, newshound, and [[alternative HTML version deleted]]

Hi, I was trying to draw a heatmap of the bicluster results. With the code given in the biclust package I can only get the heatmap for one cluster at a time (drawHeatmap function). Is there any way that I can get the heatmap for all the clusters at the same time? The code that I am using (biclust documentation) is: #Random 100x50 matrix with a single, up-regulated 10x10 bicluster

Hi, I was trying to install the package 'lme4'. Here is the code and the sessionInfo() that I am using: > install.packages("lme4",dependencies=T) Warning in install.packages("lme4", dependencies = T) : argument 'lib' is missing: using '/Users/ts/Library/R/2.11/library' Warning message: In getDependencies(pkgs, dependencies, available, lib) :