similar to: Superstring in text()

Hi Rui, Many thanks. The R code works BUT the results I get are quite weird I guess ! MIC = 0.2650 Normal 95% CI = (0.9614, 1.0398) The MIC is not inside the confidence intervals ! Is there something wrong in the R code ? Here is the reproducible example : ########## C=c(2,4,5,6,3,4,5,7,8,7,6,5,6,7,7,8,5,4,3,2) D=c(3,5,4,6,7,2,3,1,2,4,5,4,6,4,5,4,3,2,8,9) library(minerva) mine(C,D)$MIC

You need: myCor <- function(data, index){ mine(data[index, ])$MIC[1, 2] } results=boot(data = cbind(C,D), statistic = myCor, R = 2000) boot.ci(results,type="all") Look at the differences between: mine(C, D) and mine(cbind(C, D)) The first returns a value, the second returns a symmetric matrix. Just like cor() David L. Carlson Department of Anthropology Texas A&M

Hello, First of all, when I tried to use function mic I got an error. mic(cbind(C, D)) Error in mic(cbind(C, D)) : could not find function "mic" So I've changed your function myCor and all went well, with a warning relative to BCa intervals. myCor <- function(data, index){ mine(data[index, ])$MIC } results=boot(data = cbind(C,D), statistic = myCor, R = 2000)

Are there ways to load a csv file without row.names by read.csv? Thanks. [[alternative HTML version deleted]]

I would like to join repeated measures for patients across two visits using a line. The program below uses symbols to represent each patient. Basically, I would like to join each pair of symbols. library(lattice) patient <- c(1,2,3,4,5,6,7,8,9,1,2,3,4,5,6,7,8,9) var <- c(826,119,168,90,572,323,122,10,42,900,250,180,120,650,400,130,12,33) visit <- c(1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,2,2)

Dear R-Experts, Here below is my R code (reproducible example) to calculate the confidence intervals around the spearman coefficient. ########## C=c(2,4,5,6,3,4,5,7,8,7,6,5,6,7,7,8,5,4,3,2) D=c(3,5,4,6,7,2,3,1,2,4,5,4,6,4,5,4,3,2,8,9) cor(C,D,method= "spearman") library(boot) myCor=function(data,index){ cor(data[index, ])[1,2] } results=boot(data=cbind(C,D),statistic=myCor, R=2000)

I would like to set the y axis limit of an xyplot using the object 'ylimit', but receive this error: [1] 990 Error in extend.limits(limitlist[[i]], axs = axs) : improper length of lim I get the same error if I use ylim. library(lattice) trellis.device(col = FALSE, theme = lattice.getOption("col.whitebg")) name <- "Variable name" symbols <-

I have an outlier that I would still like to display, but would prefer to shorten the axis. For example, display 0% - 40%, and 90% - 100%. Is this possible? I am using an xyplot. Thanks Murray -- Murray Pung Statistician, Datapharm Australia Pty Ltd 0404 273 283 [[alternative HTML version deleted]]

Is there any way of adding text to a density plot? I have had a go using the text() function but I think the error is because this function doesn't work with densityplot(). Alternatively, I understand I can achieve pretty much the same result if I plot a density kernel estimate using plot() (which allows text()), but I do prefer densityplot(). Also, is it possible to specify the dimensions

Hi, I'm a PhD student and I want to use the function 'daisy' from the package 'cluster' to compute dissimilarities. My variables are of mixed types so I use the argument 'stand' in daisy to define the type of my variables. I have the following error message : Warning message: binary variable(s) 13, 16, 17, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,

Is it possible to add standard error bars to the means on interaction plots? Thanks Murray -- Murray Pung Statistician, Datapharm Australia Pty Ltd 0404 273 283 [[alternative HTML version deleted]]

I have checked out the help files, but cannot find details on how to use maths characters in ylab. Instead of m^2, I would like the 2 in superscript, if possible. I would also like to place more padding on the label so that the label is not obscured by the horizontal numbers. y <- 1:10 x <- rnorm(10,50000,2000) plot(x ~ y, ylab = 'Y Label (m^2)', las = 1, type =

Dear List I am new to R and to the list and will try best as I can be clear and concise. My apologies if anything I write contravenes the posting code on this list. I would also like to say I have run through most of the material on the R website before writing this email however, I am stuck. Here is what I want to do and what I have done 1. Read a comma seperated text file into R I have used

Hello, I am using function princomp from the package psych. I have my principle component object mypc: mypc <- princomp(covmat=mycor) plot(mypc) # shows me a screeplot Question: how could I actually see the values displayed in the screeplot. I don't mean on the graph - I just want to know the actual value for each component (e.g., 10, 3.2, 1.8, etc.) I need to know how much variance,

I need an object created in a user defined function to be accessible to another user defined function. I am fairly certain the object is correctly created as it prints when I use the return() function, however the 2nd function seems unable to use it. I am guessing objects created in functions are not globally accessible, is this correct? What is an appropriate way to pass the object to the

Dear R wizards, I am seeking advice on graphics in R. Specifically, how to manipulate the size and save a plot I have produced using the LDheatmap library. I confess I am relatively new to graphics in R, but I would greatly appreciate any suggestions you may have. LDheatmap produces a coloured triangular matrix of pairwise associations between 600 genetic markers in my dataset.

Hello, I have a data set with 15 variables, and use "pairs" to plot the scatterplot of this data set. Then I want to plot some circles on the small pictures with high correlation(e.g. > 0.9). First, I use "cor" to obtain the corresponding correlation matrix (x) for this scatterplot. Second, use "seq(along = x)[x > 0.9]" to find the positions of the small

Is there an implementation of the Cox-Snell residuals / Nelson-Aalen plot for goodness of fit? Or otherwise is there an appropriate Goodness of Fit diagnostic? Thanks Murray -- Murray Pung Statistician, Datapharm Australia Pty Ltd 0404 273 283 [[alternative HTML version deleted]]

I am using plot(survfit(Surv(time,status) ~...) and would like to add error bars rather than the confidence intervals. Am I able to do this at specified times? e.g. when time = 20 & 40. leukemia.surv <- survfit(Surv(time, status) ~ x, data = aml) plot(leukemia.surv, lty = 2:3,xlim = c(0,50)) #can i add error bars at times 20 & 40? legend(100, .9, c("Maintenance", "No

To differentiate between groups on the barplot, I guessed that col = colr[test$group] would have worked. How can I do this? Many Thanks Murray test <- structure(list(patient = 1:20, score = c(100, 95, 80, 75, 64, 43, 42, 40, 37, 35, 30, 29, 27, 26, 23, 22, 19, 18, 17, 16), group = c(1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 1, 0)), .Names = c("patient",