similar to: plotting 95% confidence bands on a simple linear regression model from lm()

I'd like to replace a value in a data frame with an NA, but can't figure out how. For example, say you have a<-c(1,2,3,4) b<-c(5,6,7,8) data<-data.frame(a,b) Now, how would you set the third row of the second column ( data [[3,2]] ) to NA? I have tried all types of permutations with is.na, including is.na<- data[[3,2]], which does not work. Thanks

Hi, Does anyone know how to do a coord_trans() in which the y-axis is tranformed into (for example) -1000/y? Thanks, _____________________________ Professor Michael Kubovy University of Virginia Department of Psychology USPS: P.O.Box 400400 Charlottesville, VA 22904-4400 Parcels: Room 102 Gilmer Hall McCormick Road Charlottesville, VA 22903 Office: B011

Dear r-helpers, Can anyone suggest why lm() doesn't complain here: summary(osss.lm1 <- lm(logOdds ~ c.setSize %in% task, data = osss)) whereas in package:nlme (and in package:lme4) osss.lmL <- lmList(logOdds ~ c.setSize %in% task | subj, data = osss) # Error in `contrasts<-`(`*tmp*`, value = "contr.treatment") : # contrasts can be applied only to factors with 2 or more

Hi, I would like to use the effect() function (actually a slightly modified version of it) on the output of the lmer() function in the lme4 package. But the effects package requires the nlme pacvkage, which is incompatible with lme4. Workaround? ______________________________________________ Professor Michael Kubovy University of Virginia Department of Psychology for mail add: for FedEx or

Dear R-helpers, How do I transform v <- c('insd-otsd', 'sppr-unsp') into c('insd--otsd', 'sppr--unsp') ? _____________________________ Professor Michael Kubovy University of Virginia Department of Psychology USPS: P.O.Box 400400 Charlottesville, VA 22904-4400 Parcels: Room 102 Gilmer Hall McCormick Road Charlottesville, VA 22903

Dear R-helpers, I would like the bands in an xYplot() to be gray without dark edges. I've tried playing around with col.bands, but that seems not to affect the edges, although changin col.fill does change the fill as I would expect. I would appreciate pointers. _____________________________ Professor Michael Kubovy University of Virginia Department of Psychology USPS: P.O.Box

How does one define PDFs as yet undefined in R, such as the ex- gaussian, the sum of two RVs, one exponential, one Gaussian? The PDF would then be the convolution of an exponential PDF, dexp(), and a normal, dnorm(). Kindly cc me in your reply to r-help. Thanks, _____________________________ Professor Michael Kubovy University of Virginia Department of Psychology USPS: P.O.Box 400400

library(glmmADMB) #Example for glmm.admb data(epil2) glmm.admb(y~Base*trt+Age +Visit,random=~Visit,group="subject",data=epil2,family="nbinom") Gives: Error in glmm.admb(y ~ Base * trt + Age + Visit, random = ~Visit, group = "subject", : The function maximizer failed ****************** R version 2.4.1 RC (2006-12-14 r40181) powerpc-apple-darwin8.8.0 locale: C

Dear r-helpers, Does anyone have a straightforward example of putting together three unrelated (expect for a common y-axis) xyplot() figures in what would be in base graphics a par(mfrow = c(1, 3)) arrangement? _____________________________ Professor Michael Kubovy University of Virginia Department of Psychology USPS: P.O.Box 400400 Charlottesville, VA 22904-4400 Parcels: Room 102

df1 <- data.frame(a = LETTERS[1:2], b = LETTERS[3:4], c = 1:2) I am looking for an idiom that swaps the elements of df$a and df$b when (e.g.) df$c == 2, resulting in df2 <- data.frame(a = LETTERS[c(1, 4)], b = LETTERS[c(3, 2)], c = 1:2) _____________________________ Professor Michael Kubovy University of Virginia Department of Psychology USPS: P.O.Box 400400 Charlottesville, VA

What am I doing wrong? > install.packages("Hmisc") trying URL `http://cran.r-project.org/src/contrib/PACKAGES' Content type `text/plain; charset=iso-8859-1' length 47565 bytes opened URL ================================================== downloaded 46Kb trying URL `http://cran.r-project.org/src/contrib/Hmisc_3.0-1.tar.gz' Content type `application/x-tar' length

Dear Friends, Here is an algorithm for finding concave hulls: http://get.dsi.uminho.pt/local/ Has anyone implemented such an algorithm in R? RSiteSearch('concave hull') didn't reveal one (I think). _____________________________ Professor Michael Kubovy University of Virginia Department of Psychology Postal Address: P.O.Box 400400, Charlottesville, VA 22904-4400 Express Parcels

Dear R-helpers, It is not clear to me how you get measurement.error SD when you have a single dataset, and it is not clear to me how sensitive SIMEX is to errors in the estimates of measurement error. Could someone please point me to the relevant literature? _____________________________ Professor Michael Kubovy University of Virginia Department of Psychology USPS: P.O.Box 400400

hi, is there an option to calculate the 'within' & 'between' group variances for a simple ANOVA (aov) model (2 groups, 1 trait, normally distr.) ? or do I have to calculate them from the Sum Sq ? thanks for your time and greetings, gregor -- Gregor Rolshausen PhD Student; University of Freiburg, Germany e-mail: gregor.rolshausen at biologie.uni-freiburg.de tel. :

Dear Friends, I not sure whether this is an Sweave or a beamer problem. The Rnw file: \documentclass[compress,smaller]{beamer} %\documentclass{article} %\usepackage{beamerarticle} \usepackage{Sweave} \title{Psychophysics II} \date{September 9, 2008} \begin{document} \frame{ \begin{Schunk} \begin{Sinput} > ro <- 0.2 > c <- seq(from = -3, to = 4, by = 0.1) > fn <- 1 -

Dear r-helpers, xx <- c(0.000, 0.210, 0.714, 0.514, 1.000, 0.190, 0.590, 0.152) yy <- c(0.000, 0.265, 0.256, 0.521, 0.538, 0.761, 0.821, 1.000) aa <- c(19, 19, 19, 21, 19, 21, 21, 21) x0 <- xx[c(1, 1, 2, 2, 2, 3, 3, 4, 4, 4, 5, 6, 6, 7)] y0 <- yy[c(1, 1, 2, 2, 2, 3, 3, 4, 4, 4, 5, 6, 6, 7)] x1 <- xx[c(2, 3, 3, 4, 6, 4, 5, 5, 6, 7, 7, 7, 8, 8)] y1 <- yy[c(2, 3, 3, 4, 6, 4, 5,

Dear R readers: I have written a short lme.R function, which adds normalized coefficients and White heteroskedasticity-adjusted statistics to the standard output. Otherwise, it behaves like lm. This is of course trivial for experts, but for me and other amateur users perhaps helpful. y= rnorm(15); x= rnorm(15); z= rnorm(15); m= lme( y ~ x + z); print(summary(m)); produces something

I need to extract the p value from a ANOVA done with lm model fitting <- lm(var ~ group) Sfitting <- summary(fitting) Sfitting[10][1] gives the F value and the degrees of freedom but I am not able to get the p value. The function df should give a p value given a F but I am not able to make it work. I found only something about aov in the R help and I am not able to make it work Massimo

Dear r-helpers, tst <- data.frame(as.numeric(x <- 1:20), f <- rep(c('hi','lo'), times = 10)) with(tst, bwplot(f ~ x, panel = function(x, y){panel.bwplot(x, y, pch = '|', stats = boxplot.stats, fill = 8, varwidth = T)})) I can't figure out from the documentation how to tell stats that I would like to see notches or (even bands). Here is what I've

Dear R-listers, Can someone suggest a method for generating a finite Bernoulli sequence that is likely to have a given point-biserial correlation with an existing Bernoulli sequence? _____________________________ Professor Michael Kubovy University of Virginia Department of Psychology USPS: P.O.Box 400400 Charlottesville, VA 22904-4400 Parcels: Room 102 Gilmer Hall