similar to: ecdf

Dear R experts, Might be very simple question to ask but would be insightful. As the same story of nested "for loops". following is the code that I am using to get the autocorrelation function of the sample data. I have tried to get rid of for loops but since I am touching R after such a long time that I need to practice more but I need help to revive my skills. I know that apply() or

Hi All, I am running an Rscript with a bunch of algorithms that are UNSTABLE under some parameter settings. At a certain point one of them sends error massage and my whole run STOPS! What I would like is to save the error massage in some file or variable and carry on to the next command line without stopping this run... Any help or ideas would be welcome, please, with a concrete example (not

Hi, I have following codes : library(zoo); library(ggplot2); library(plyr) dat <- rnorm(306); vv <- letters[1:6]; dat1 <- data.frame(dat, vv) dat2 = zooreg(rnorm(51), as.yearmon(as.Date("2000-01-01")), frequency=12) ggplot(dat1) + geom_line(aes(y=dat, x=index(dat2), colour=vv), group=vv, size = 1.3) However I got error while plotting them :

Hello, is it possible to create two uncorrelated random vectors for a given distribution. In fact, I would like to have something like the function "rnorm" or "rlogis" with the extra property that they are uncorrelated. Thanks for your help, Luba [[alternative HTML version deleted]]

is there a way to reduce the size of pdf files in R: ? compression? lower dpi ? or some other option?

Dear All, This may sound like a dumb question but I am trying to use a mixed model to determine the predictors of bat activity along hedges within 8 sites. So my response is continuous (bat passes) my predictors fixed effects are continuous (height metres), width (metres) etc and the random effect is site - can you tell me if the fixed effects can be continuous as all the examples I have

Hi List, I am running R 2.8.0 on a Windows XP machine, running ggplot2 version 0.8.1 I want to label the bars in a faceted grid barplot. Reproducible R code is given below: #### reproducible facet barplot ##### library(ggplot2) # Dataset from which to create the barplot ml <- rep(1:10,2) vals <- rnorm(20,mean = 10, sd=1) type <- c(rep("MAPE",10),rep("AIC",10))

Dear all, One of the functions that I wrote (ggsave.latex) extents the functionality of a function (ggsave) in another package (ggplot2). Instead of copying all the information I would like to create a link in the helpfile of ggsave.latex to the helpfile of ggsave. I tried \code{\link{ggsave}} and \code{\link{ggplot2::ggsave}}, but neither worked. Both cases gave a 'missing link' warning.

Dear useRs, I want to plot the following barplot with lines instead of bars. Is there a way? data <- data.frame(cbind(k = 0:3, fk = c(11, 20,7,2), f0k = c(13.72, 17.64, 7.56, 1.08), fkest = c(11.85, 17.78, 8.89, 1.48))) d <- t(data[,2:4]) barplot(d, beside=TRUE) Regards, Rafael. ____________________________________________________________________________________ [[elided Yahoo

Dear all, I'm not getting what I'm doing wrong. The line below from my read.fsa.bin function throws an error when just loading my AFLP package and disappears when I load the zoo package as well. #the line that throws the error Index <- which(Peak == rollmax(Peak, k = 1 + 2 * floor((min(diff(SizeStandard)) * Fs - 1) / 2), fill = -Inf)) #the error Error in UseMethod("rollmax")

Full_Name: Paul Eckermann Version: 2.7.1 OS: Windows XP Service Pack 2 Submission from: (NULL) (129.127.183.12) This is the first time I have submitted a bug report, so apologies if I have not followed the correct protocol. If I enter length(rnorm(100*.29)) it returns 28 rather than 29. y<-(1:100)/100 z<-sapply(y,function(x) length(rnorm(x*100))) z!=100*y indicates that it has

Dear all, I'm plotting some points on a graph where both axes need to have the same scale. See the example below. Coord_equal does that trick but in this case it wastes a lot of space on the y-axis. Setting the limits of the y-axis myself was no avail. Any suggestions to solve this problem? library(ggplot2) ds <- data.frame(x = runif(1000, min = 0, max = 300000), y = runif(1000, min =

Dear all, I have a list of n matrices which all have the same dimension (r x s). What would be a fast/elegant way to calculate the element wise average? So result[1, 1] <- mean(c(raw[[1]][1, 1] , raw[[2]][1, 1], raw[[...]][1, 1], raw[[n]][1, 1])) Here is my attempt. #create a dummy dataset n <- 3 r <- 5 s <- 6 raw <- lapply(seq_len(n), function(i){ matrix(rnorm(r * s), ncol =

Hi, I've three values. What is the best method to choice the lowest values with an if function? example: a = 3 b = 1 c = 5 if (lowest(a,b,c) is a) {........} if (lowest(a,b,c) is b) {........} if (lowest(a,b,c) is c) {........} Thanks, Alfredo

Hi, I'm trying to fit a smooth line in a plot(y ~ x) graph. x is continuous variable y is a proportion of success in sub-samples, 0 <= y <= 1, from a Monte Carlo simulation. For each x there may be several y-values from different runs. Each run produces several sub-samples, where "0" mean no success in any sub- sample, "0.5" means success in half of the

Hi all, i have a pretty easy indexing question, at least i believe so. The main reason i post it here, is that brackets and $ are hard to google. How do I index correctly, if i just want to display the whole dataset conditioned on the fact that some particular column equals one. I know i can do something like: data$somecolumn[data$particularcol ==1] . That will show all "some

Dear R help group, I am teaching myself linear mixed models with missing data since I would like to analyze a stats design with these kind of models. The textbook example is for the procedure "proc MIXED" in SAS, but I would like to know if there is an equivalent in R. This example only includes two time-measurements across subjects (a t-test "with missing values"), but I

Hi Duncan I tried Ecdf and/or wtd.quantile from Hmisc and it is working (probably). Ecdf(x, q=.5) Ecdf(x, weights=xw,col=2, add=T, q=.5) wtd.quantile(x) 0% 25% 50% 75% 100% 10 10 10 100 300 wtd.quantile(x, weights=xw, type="i/n") 0% 25% 50% 75% 100% 10.0000 138.8667 192.5778 246.2889 300.0000 But could you please be more specific in this? >

Dear all, Could someone point me to a function or algorithm to generate random bivariate binomial data? Some details about what I'm trying to do. I have a dataset of trees who were categorised as not damaged or damaged. Each tree is measured twice (once in two consecutive years). The trees can recover from the damage but the data is clearly correlated. As a (un)damaged tree is more likely

Hello, I am trying to build a generalised linear mixed model.? My dependent variable is ordinal.? I have a random factor (7 individuals), and a repeated measure where the dependent variable was measured three times for each of four attempts (so the repeats are nested).? I also have a few covariates.? I am a complete novice in R, being used to using SPSS.? SPSS lets me build an ordinal model