similar to: looking for the na.omit equivalent for a matrix of characters

I've searched for the answer to this in the help list archive, but wasn't able to get the answer to work. I'm interested in converting a row of a data.frame into a vector. However, when I use as.vector(x,[1,]) I get another data.frame, instead of a vector. (On the other hand, when I use as.vector(x,[,1]), I get a vector.) Thanks, Andrew [[alternative HTML version deleted]]

I am converting some matlab code into R that use inverse of the complementary error function, erfcinv and did not find an equivalent in R, is there such a function in some contributed modules? Thanks.

I have a big contingency table, approximately of size 60*2*500*500, and I need to count the number of cells containing a count of 1 for each of the factors values defining the first dimension. Here is my attempt: tab1<-with(pisa1,table(CNT,GENDER,ISCOF,ISCOM)) tab2<-apply(tab1,1:4,function(x)ifelse(sum(x)==1,1,0)) tab3<-apply(tab2,1,sum) Computing tab2 is very slow. Is there a faster

I found writing the following default method the for the generic function "julian" causes R to crash. julian.default <- function(x, ...) { x <- as.Date(x) NextMethod("julian", x, ...) } Here is a test example > m <- as.Date("1972-09-27") + 0:10 > m [1] "1972-09-27" "1972-09-28" "1972-09-29"

I am hoping for some advice regarding resolving error messages I have received when trying to use the expand.grid command. library(nnet) library(MASS) library(car) mod.multacute <-multinom(kc$group ~ kc$in.acute.danger * kc$violent.convictions, na.rm=T) summary(mod.multacute, cor=F, Wald=T) Anova (mod.multacute) confint (mod.multacute) > predictors <- expand.grid(group=1:3,

Hi R, I wanted to know how do we access the elements of a list. In particular, v=list(c(1,2,3,4,5),c(1,2,33,4,5),c(1,2,333,4,5),c(1,2,3333,4,5)) I want to access all the thirds items of the elements of the list. i.e., I want to access the elements, 3,33,333,3333. This can be done through sapply as: sapply(v,function(x) x[3]) But I need to access this without using

While termplot is under discussion, here's another proposal. I'd like to change the default for partial.resid to TRUE, and for smooth to panel.smooth. I'd be surprised if those changes were to break existing code. John Maindonald email: john.maindonald at anu.edu.au phone : +61 2 (6125)3473 fax : +61 2(6125)5549 Centre for Mathematics & Its Applications, Room

The function "substitute" seems to fail to make a genuine substitution, although the printed verision seems fine. Here is an example. > m <- substitute(Y <- function(x) FUN(x+1), + list(Y = as.name("y"), FUN = as.name("sin"))) > m y <- function(x) sin(x + 1) > eval(m) > y function(x) FUN(x+1) However the story doesn't end there. The

I have a set data={A,B,C,D,E,F,G} I want to choose 2 letter from 8 letters, i.e. generate the combination set for choose 2 letters from 8 letters. I want to get the liking: combination set={AB,AC,AD,....} Does anyone konw how to do in R. thanks, Aimin

I have just become painfully aware that objects of class "difftime", generated by the difference of two POSIXct objects, carry a "units" attribute, which flashes by when the object is printed, for example. The pain was occasioned when I tried to turn these objects into numberic objects for use elsewhere as a covariate. as.numeric(difftime object) simply turns off the units

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Hi I would like to sum a number of time series, some of them having NA's Standard action is here that if I sum a value with a NA, then the result is NA. I would like it to just keep the value. I then try to: a = NA; if (a == NA) { a = 0} just to try it out, but it says Error in if (a == NA) { : missing value where TRUE/FALSE needed What is wrong, and can I do it smarter? I looked at

This is not so much a bug as an infelicity in the code that can easily be fixed. The initialize expression in the quasi family function is, (uniformly for all links and all variance functions): initialize <- expression({ n <- rep.int(1, nobs) mustart <- y + 0.1 * (y == 0) }) This is inappropriate (and often fails) for variance function "mu(1-mu)".

Does anyone have, or has anyone ever considered making, a version of 'termplot' that allows the user to specify that all plots should have the same y-limits? This seems a natural thing to ask for, as the plots share a y-scale. If you don't have the same y-axes you can easily misread the comparative contributions of the different components. Notes: the current version of termplot

Does anyone have, or has anyone ever considered making, a version of 'termplot' that allows the user to specify that all plots should have the same y-limits? This seems a natural thing to ask for, as the plots share a y-scale. If you don't have the same y-axes you can easily misread the comparative contributions of the different components. Notes: the current version of termplot

Hi, I can not comprehend the linear fitting results of polynoms. For example, given the following data (representing y = x^2): > x <- 1:3 > y <- c(1, 4, 9) performing a linear fit > f <- lm(y ~ poly(x, 2)) gives weird coefficients: > coefficients(f) (Intercept) poly(x, 2)1 poly(x, 2)2 4.6666667 5.6568542 0.8164966 However the fitted() result makes sense: >

hi, I am reading Modern Applied Statistics with S 4th ed$B!#(B page4 have these two lines: > library(MASS) > data(chem) # needed in R only but I find withou the line " data(chem)" I can still access chem, isn't it? is it unnecessary or something i missed here? thanks for the replay in advance.

At 14:35 02/10/00 +0800, mohd zamri wrote: >new to R and starting to learn to program R. The underscore ("_") did some >suprising result. e.g > >> c <- c(1,2,3,4,5) >> mean(c) >[1] 3 >> c_mean <- mean(c) >> c >[1] 3 > >having some experience in C, I thought the underscore is "always" valid in >variable name. totally confuse

Hi all, I will be teaching a graduate-level course on R at CU Boulder next semester. I have a teaching idea that might also help improve the R wiki page... I wanted to know what you all thought of it and wanted to solicit some advice about doing it. During the latter part of the course, students will choose a topic of interest (e.g., hierarchical linear modeling), and show how to achieve it in

When doing polynomial regression I believe it is a good idea to use the poly function to generate orthogonal polynomials. When doing this in Splus there is a handy function (transform.poly I think) to convert the coefficients produced by regression with the poly function back to the original scale. Has somebody written something similar for R ? Robert