You might want to try a logistic regression model to predict the binary response as a function of your continuous predictor. You can then select a cut point for your predictor variable to define a bi
You need to add keep.xy=T to your function call because your function has extra arguments in addition to x (see help page on uniroot): uniroot(f = SeuilGamma, lower = 440, upper = 450, + f.lower = -0
5 x[!duplicated(x)] a b c 3 4 5 -Christos From: s-news-owner@lists.biostat.wustl.edu [mailto:s-news-owner@lists.biostat.wustl.edu] On Behalf Of Leeds, Mark Sent: Saturday, June 11, 2005 11:48 PM To:
I need to estimate the power of a test for gene selection based on a rank-based criterion as a function of sample size using data from a pilot study. The pilot study has N=200 samples and I would li
You can get square plots by setting the global parameter pty before plotting: ) # reset to rectangular plots -Christos From: s-news-owner@lists.biostat.wustl.edu [mailto:s-news-owner@lists.biostat.wu
Thank you Dimitris and Eric for your prompt answer. This works perfectly. I wasn't aware of the do.call function. -Christos --Original Message-- From: Dimitris Rizopoulos [mailto:dimitrios.rizopoulos
This works in R - don't have S-Plus loaded any more: df <- rbind(1:4,LETTERS[1:4],5:8,letters[1:4]) df[ rep(c(1:nrow(df)),each=3), ] -Christos --Original Message-- From: s-news-owner@lists.biostat.wu
You can try this: ones <- matrix(1,4,3) B <- t(t(ones) * c(2,4,3)) A-B should give you the desired result, where A is your original matrix. -Christos Dear Users I have a matrix (4x3) 4 5 6 2 4 5 2 4
You need to look into multidimensional scaling (MDS). If you have the MASS4 book handy (Venables & Ripley) take a look at Chapter 11. There is a lot of background materials and several examples. You