similar to: grouping values

Any better solution than this ? sum(strsplit("TCGGGGGACAATCGGTAACCCGTCT", "")[[1]] == "G") _________________________________________________________________ [[alternative HTML version deleted]]

Dear all, I would like to generate 25 numbers from 1 to 100 but I would like to have some numbers that could be more probable to come out. I was thinking of the function runif: runif(25, 1, 100) , but I don?t know how to give more weight to some numbers. Example: each number from 2 to 10 has the probability of 40% to come out but the probability of each number from 11 to 100 to come out is

Must packages in the Depends field of the DESCRIPTION file have NAMESPACES? I haven't seen this explicitly indicated anywhere. I am writing a small package and find that when I add the abind package to the list of the Depends field, I get an error in R CMD check of the build. * checking package name space information ... OK * checking package dependencies ... ERROR Packages required but not

Hi, I'm trying to redefine the contrasts for a linear model. With a 2 level factor, x, with levels A and B, a two level factor outputs A and B - A from an lm fit, say lm(y ~ x). I would like to set the contrasts so that the coefficients output are -0.5 (A + B) and B - A, but I can't get the sign correct for the first coefficient (Intercept). Here is a toy example, set.seed(12161952) y

Hi all I am one recent user of R and have a few doubts I did a binomial GLM with 3 - factor and now I have to test contrasts to identify that treatments are different. I know that the contrasts are used in ANOVA, it is not incorrect to use them in GLM? there is a way to do contrasts between treatments for GLM as a Tukey for the ANOVA? Susana

I would like to do an R glm() with family = binomial(link="loglog") Right now, the cloglog link exists, which is nice when the data have a heavy tail to the left. I have the opposite case and the loglog link is what I need. Can someone suggest how to add the loglog link onto glm()? It would be lovely to have it there by default, and it certainly makes sense to have the two opposite

Hi all, I am trying to parse a vector for caliculating minimum in that vector the vector having values like 1 Kontrolle 2 Placebo 3 125mg/kg 4 250mg/kg 5 500mg/kg 6 1000mg/kg hear i tries for comverting it into numeric with using "as.numaric()" function but i got values like 5 6 2 3 4 1 it gives 1000mg/kg is the least one but i have

Hi folks, I've just discovered that the following code leads to boxplot (surprisingly to me). Can anybody explain to me why? Is this documented somewhere? I've never consider this option before. x <- rnorm(300) l <- c(rep("label1",100), rep("label2",50), rep("label3",150)) df <- data.frame(as.factor(l), x) plot(df) Thank you! Antje

I'm using scan in a script to record a series of responses of the user as a function of some graphs that I put up on the screen. A toy version would be, y <- rep(NA, 3) for (ix in seq( length(y) ) ) { y[ix] <- scan( n = 1 ) } However, if I include any code after this loop, for example, y <- rep(NA, 3) for (ix in seq( length(y) ) ) { y[ix] <- scan( n = 1 ) } y I get an error

Hi all, I've noticed that many computational neuroscience research groups use MATLAB. While it's possible that MATLAB may have some features unavailable in R, I suspect that this may instead simply be a case of costly tradition, where researchers were taught MATLAB as students and pay for it as researchers because it's all they know. I'd like to attempt to break the cycle by

Dear, I am trying to get a prediction of my GAM on a response type. So that I eventually get plots with the correct values on my ylab. I have been able to get some of my GAM's working with the example shown below: * model1<-gam(nsdall ~ s(jdaylitr2), data=datansd) newd1 <- data.frame(jdaylitr2=(244:304)) pred1 <- predict.gam(model1,newd1,type="response")* The problem I am

Hi all, Where f(x) is a logistic function, I have data that follow: g(x) = f(x)*.5 + .5 How would you suggest I modify the standard glm(..., family='binomial') function to fit this? Here's an example of a clearly ill-advised attempt to simply use the standard glm(..., family='binomial') approach: ######## # First generate some data ######## #define the scale and location of

I would like to suppress the text 'Scatter Plot Matrix' that appears under the plot. Could someone please suggest how? _____________________________ 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

Hi all, I have a rather naive question. I have the height of 100 individuals in a table and I want to assign the tallest 30% as Case=1 and the bottom 30% as Case=0. How do I do that? thanks. jiong The email message (and any attachments) is for the sole use of the intended recipient(s) and may contain confidential information. Any unauthorized review, use, disclosure or distribution is

Dear r-helpers, I wonder whether, given the "#rrggbb" representation of a colour, there is a simple way to select the complementary colour, also expressed as a "#rrggbb" string. Any suggestions would be appreciated. John -------------------------------- John Fox, Professor Department of Sociology McMaster University Hamilton, Ontario Canada L8S 4M4 905-525-9140x23604

Hi, I was taken off guard by the following behavior in a lattice plot. I frequently want to add a predicted curve defined at more points than in the formula expression of xyplot. There have been numerous examples of how to do this on r-help, but I still often struggle to make this work. I just realized that specifying one of the axes on a log scale does not guarantee that the added data for a

I've just started using R and am still a neophyte, but I found the following curious result. I'm using the current version of R (2.5.1 (2007-06-27) ). Why are the results for the third quartile different in the output from the summary and fivenum commands? For the following data set 457 514 530 530 538 560 687 745 745 778 786 790 792

Hi, Is there a function for raising a matrix to a power? For example if you like to compute A%*%A%*%A, is there an abbreviation similar to A^3? Atte Tenkanen > A=rbind(c(1,1),c(-1,-2)) > A [,1] [,2] [1,] 1 1 [2,] -1 -2 > A^3 [,1] [,2] [1,] 1 1 [2,] -1 -8 But: > A%*%A%*%A [,1] [,2] [1,] 1 2 [2,] -2 -5

Hi, I'm fitting a standard nonlinear model to the luminances measured from the red, green and blue guns of a TV display, using nls. The call is: dd.nls <- nls(Lum ~ Blev + beta[Gun] * GL^gamm, data = dd, start = st) where st was initally estimated using optim() st $Blev [1] -0.06551802 $beta [1] 1.509686e-05 4.555250e-05 7.322720e-06 $gamm [1] 2.511870 This works fine but I

Greetings, everyone. I've been trying to analyze bird nest survival data using generalized linear mixed models (because we documented several consecutive nesting attempts by the same individuals; i.e. repeated measures data) and have been unable to persuade the various GLMM models to work with my user-defined link function. Actually, glmmPQL seems to work, but as I want to evaluate a suite of