similar to: bootstrap proportions?

This has been asked before, but all the answers are hidiously complex. The legend.text=TRUE option of barplot is almost exactly what I need, except I need a legend.placement='tl' (top left) option. This option would be in contrast to the default placement which we could call 'tr' (top right). Anyone know how to edit the barplot code to make this change? Could someone like me

Signif. codes: 0 *** 0.001 ** 0.01 * 0.05 . 0.1 1 Signif. codes: 0 <80><98>***<80><99> 0.001 <80><98>**<80><99> 0.01 <80><98>*<80> <99> 0.05 <80><98>.<80><99> 0.1 <80><98> <80><99> 1 Signif. codes: 0 *** 0.001 ** 0.01 * 0.05 . 0.1 1 hmm... they go away when I

I found that the edit command kills my linux/R/emacs environment sometimes. How should I report this bug?

I read answers to questions including the words "tapply" and "weighted.mean", but I didn't understand either the problem (data) or the solution provided. Here is my question ... > dat[1:10,] GROUP VALUE FREQUENCY 1 2 2 78 2 2 3 40 3 2 4 16 4 2 5 3 5 2 6 1 6 2 8 1 7

Is there an R wiki? Looking at the huge amount of traffic on this list, I think wiki could be an exelet outlet for all the constructive enthusiasm here. I don't think it would be too hard to port the existing R documentation (the stuff you get with the ?) onto a wiki system, then users could add their own examples and comments. Having distinct web page style organization would be easier to

Hi, Since I started to make some 'final' plots of my data I found that I have tons of questions related to 'the little things'. Rather than bother the list with all the questions (ahem), or search the archives for similar questions and translate the context, I would like to find a FAQ for plotting in particular (and R programming in general). I know for sure (searching the

Hello, supposing that I have two or three clear categories for my data, lets say pet preferece across fish, cat, dog. Lets say most people rate their preference as being mostly one of the categories. I want to do pca on the data to see three 'groups' of people, one group for fish, one for cat and one for dog. I would like to see the odd person who likes both or all three in the

I want to add values onto the end of a vector, for example... x <- vector for (i in 1:5){ add_to_end_of_vector(i,x) } I just cant find the answer to this question! Sorry for such a basic question, I tried... x <- c() for (i in 1:5) x[length(x)] <- i but it didn't work.

I store an id as a big number, could this be a problem? Should I convert to at string when I use read.table(... example id's 1001001001001 1001001001002 ... 1002001002005 Bigest is probably 1011001001001 Ta, Dan.

I use the following code to scan a (limited) parameter space of clustering strategies ... data <- read.table(... dataTranspose <- t(data) distMeth <- c("euclidean", "maximum", "manhattan", "canberra", "binary" ) clustMeth <- c("ward",

I am trying the following code... for(i in 1:bins){ print(cat(c(i, length(var1[var1==i])))) } Where var1 is a vector with zero or more values = {1, 2, ..., bins} (or something like that). The result I get is... 1 33NULL 2 28NULL 3 39NULL 4 27NULL 5 32NULL 6 30NULL 7 23NULL 8 16NULL 9 10NULL 10 15NULL 11 13NULL 12 7NULL 13 3NULL 14 7NULL 15 2NULL 16 0NULL 17 2NULL 18 0NULL 19 0NULL 20 3NULL

what about using "mapply"? splitted.value<-with(x.1, split(VALUE, GROUP)) splitted.freq<-with(x.1, split(FREQUENCY, GROUP)) mapply(weighted.mean, splitted.value, w=splitted.freq) Stefano >-----Messaggio originale----- >Da: r-help-bounces at stat.math.ethz.ch >[mailto:r-help-bounces at stat.math.ethz.ch]Per conto di >james.holtman at convergys.com

Full_Name: Dan B Version: na OS: na Submission from: (NULL) (80.6.127.185) I can't log into the bug tracker (I can't find where to register / login). In this way I can't add the following context diff (hopefully in the right order) for my changes to the matrix.Rd... Hmm... I guess this should be a separate report anyway... The first diff explains how the dimnames list should

Hi, I want to use hist with non-equi-spaced breaks, picked such that the fraction of the data points falling in the cells (defined by 'breaks') is roughly equal accross all cells. Is there such a function that will automatically try to determine the breaks to fullfill this requirement? Something like.. hist( x, br = magic_function_to_pick_breaks()) For example, if x looked like

Gives strange results. I get 'weird' dendrograms with canberra / binary distance metric and median / centroid cluster methods. Is this just my data? Dan

I found this great search source("http://www.statslab.cam.ac.uk/~djw1005/Stats/Interests/search.R") helpHTML() Has (or will) this become the standard search method? Is R 'Free Software'? The dependence on Java seems a bit of a pain for 'freeness'. Did the above make it into CRAN? Cheers, Dan.

Meta: This question is somewhat long and has two parts, I would be very happy for someone just to nudge me in the right direction with the manual / tutorial, as I am somewhat lost... 1) How do I fit a curve of the form "y = k1 * x^k2" ? I want to estimate values of k1 and k2 given the x/y data I have, and I can't work out how to get R to calculate and return their estimates. 2)

Martin Maechler said... > >>>>>> "lanceh" == lanceh <lanceh at ibm.net> writes: > > lanceh> Sorry if this is a redundent question but I searched the > lanceh> archives and although I found a couple of similar questions I > lanceh> saw no responses. I am running in Linux and when I try to > >You should have looked in the

Dear all, Does someone know an R function implementing the method of Sison and Glaz (1995) (see full ref below) for computing Simultaneous confidence intervals for multinomial proportions? As alternative method, I think to boostrap the mean of each proportion and get in that way confidence interval of the mean. I observed 21 times a response that could be one out of 8 categories

Hi everyone, I've searched the internet and lots of stats books high and low for this one, but nothing seems to be quite what I want. I've got continuous data on four different state activities recorded in seconds, however each continuous session is not equally long, so the data are best expressed as proportions, i.e.: Subject 1: Swimming, 0.5, Hiding, 0.25, Edge, 0.125, Inactive, 0.125