similar to: weighted.mean and tapply (again)

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

Hi, I recently encountered an error using the command "savePlot" when trying to save the third of 3 open graph windows. After successfully saving and closing the first two windows I receive an "Invalid device number in savePlot" error. The following is copied and pasted from an example session to illustrate the behaviour: > windows() > hist(rnorm(100)) > windows()

I am trying to calculate the weighted mean for a of 10 deciles and I get an error: > decile <- tapply(X=mat$trt1m, INDEX=mat$Rank, FUN=weighted.mean, w=mat$mcap) Error in FUN(X[[1]], ...) : 'x' and 'w' must have the same length All three of my inputs have the same length, as shown below, and the weighted.mean calculation works by itself, just not in tapply() >

I' m trying to compute weighted mean on different groups but it only returns NA. If I use the following data.frame truc: x y w 1 1 1 1 2 2 1 3 1 1 4 2 0 2 1 0 3 2 0 4 1 0 5 1 where x is a factor, and then use the command : tapply(truc$y,list(truc$x),wtd.mean, weights=truc$w) I just get NA. What's the problem ? What can I do ?

Hello! I have data frame with 'weights' in one of the columns. I need to compute weighted mean on another column other factor variable and i am trying to: res<-tapply(data$k,list(data$model),weighted.mean,w=data$w,na.rm=T) and i get: Warning messages: 1: longer object length is not a multiple of shorter object length in: x * w 2: longer object length is not a multiple of shorter

We were caught out recently attempting to use tapply to get a table of weighted means. This gives the wrong answer (or, more correctly, not the answer we were expecting), as the following example shows: R> x <- 1:10 #some data R> w <- c(1:5,5:1) #weights R> id <- rep(1:2,rep(5,2)) #id values R> weighted.mean(x[id==1],w[id==1]) #Weighted mean of x in group 1 [1] 3.666667

I am trying to use tapply to estimate the average wage in a set of Year*Education cells using sampling weights, as well as some other other statistics using the weights). I am having trouble trying to figure out how to pass the weights to the function, using: > tapply(wage,list(Educc,Year),weighted.mean, w=weight) whieh produces warnings of the type: 3: longer object length is not a

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

hi all, It's not clear to me how (or if) I can pass multiple values for lty to a key in xyplot? I've tried: lines=list(lty=1:3), to no avail. Do I need to use something other than auto.key? (Deepayan, if you're out there, I have your book and must admit the answer isn't jumping out at me.) thanks in advance! Michael Folkes example code: #____________________________

Hello all, I've been using binconf (package Hmisc) at a range of alpha values and noticed that using the 'Wilson' method when alpha is larger (i.e. narrow CI), results in the upper value being smaller than the lower value. The 'exact' and 'asymptotic' methods give results in the realm I'd expect. But the help file suggests: "Following Agresti and Coull, the

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

Hello all, It seems that the next improvement to the R Graph Gallery is categorization of the graphics, that way each graph will be easier to find. That step should be done *carefully* if we want to avoid the opposite side-effect : graph not reachable through the categories. That's why the wisdom of the R community is required. Graphics will be classified in : - categories -

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

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

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.

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

The following single line of code shows what I am trying to do, and the problem I am having... barplot(c(101,102,103),ylim=c(100,103)) The 'xaxis' is missing, and the grey bars 'fall off' the plot area. This is generally ugly, and I would like to trim the bars (ideally they would have a ragged appearance to show that I am 'zooming in'). I can see why what I am trying to

Hi I am trying to install Samba on a QNX 4.24 system. When we run the make file we get an error : compiling server.c make:cc:command not found make: *** [server.o] error 127 Can you help with this! Lucille Shears Systems Analyst CCG/DFO shearsl@dfo-mpo.gc.ca (709) 772-3131 cell (685-1512)

Perhaps somebody could clarify for me if the following is a floating point matter or otherwise, and how am I to correct for it? > floor(100*.1) [1] 10 > 100*(1.0-.9) [1] 10 > floor(100*(1-0.9)) [1] 9 Thanks! Michael _______________________________________________________ Michael Folkes Salmon Stock Assessment Canadian Dept. of Fisheries & Oceans Pacific Biological Station

Hi, I believe this question has been asked before, but I cant find and don't remember the answer. The problem is simple, calling 'plot.data.frame(x)' gives a nice 'matrix of scatterplots' for each pair of columns in x. for example; x <- data.frame(a=jitter(01:20), b=jitter(20:01), c=jitter(21:40), d=jitter(rep(01,20)),