similar to: A easy way to write formula

Dear all, I have encountered a problem when perform stepwise regression. The dataset have more 9 independent variables, but 7 observation. In R, before performing stepwise, a lm object should be given. fm <- lm(y ~ X1 + X2 + X3 + X11 + X22 + X33 + X12 + X13 + X23) However, summary(fm) will give: Residual standard error: NaN on 0 degrees of freedom Multiple R-Squared: 1, Adjusted

Hi, I would like to ask for advice about best statistics method for my problem. I was done questionnaire about headache. My data are: Y - frequency of symptoms occur - times per month in range <0..30> (where 30 is daily and zero for never) and independent variables: X1 - sex - category {M,F} X2 - age - linear value X3 - type of work {administrative, manual, ...} ... Which model is

Dear All, I wonder if there is any R function to generate a sequence of vectors from existing ones. For example: x 1<- c(1,2,3) x2 <- c(4,5) x3 <- c(6,7,8) The desired output is a list of all 3*2*3 = 18 possible combinations of elements of x1,x2 and x3. One element for example is (1,4,6). Many thanks in advance, Bernard

Hi there, I am a Chinese R user. I hope to display Chinese character in a plot, and than save it in PostScript format. I have read the article titled "Non-Standard Fonts in PostScript and PDF Graphics", especially the section about CJK fonts. I also tried the code: > pdf("chinese.pdf", width=3, height=1) > grid.text("\u4F60\u597D", y=2/3,

Don't do this (sorry Thierry)! max() already does this -- see ?max > x <- data.frame(a =rnorm(10), b = rnorm(10)) > max(x) [1] 1.799644 > max(sapply(x,max)) [1] 1.799644 Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic

The maximum over twelve columns is the maximum of the twelve maxima of each of the columns. single_col_max <- apply(x, 2, max) twelve_col_max <- apply( matrix(single_col_max, nrow = 12), 2, max ) ir. Thierry Onkelinx Statisticus / Statistician Vlaamse Overheid / Government of Flanders INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND FOREST Team Biometrie

Dear all, I have monthly data in wide format, I am only providing data (at the bottom of the email) for the first 24 columns but I have 2880 columns in total. I would like to take max of every 12 columns. I have taken the mean of every 12 columns with the following code: byapply <- function(x, by, fun, ...) { # Create index list if (length(by) == 1) { nc <- ncol(x)

Hi there, I searched R-help list with "path analysis" as keyword, and learn that sem package can do it. However, I don't figure out a way to construct the model for the path diagram as Fig. 1. in Huang et al. (2002)[1]. I try the following code: huang.cor <- readMoments(diag=FALSE, names=c('x1', 'x2', 'x3', 'y')) 0.76 0.91 0.72 0.94 0.77 0.83

Hi there, I hope to build a model Y ~ X1 + X2 + X3 + X4 with X1 has two instrumental variable A and B, and X2 has one instrumental variable A. I have searched the R site and mailling list, and known that the tsls() from sem package and ivreg() from AER package can deal with instrumental variable regression, however, I don't know how to formula the model. Any suggestion will be really

Hi there, According to ?par, 'font' is an integer which specifies which font to use for text, that 1 corresponds to plain text (the default), 2 to bold face, 3 to italic and 4 to bold italic. When I test Chinese character in pdf(), I found that 1 to bold face, 2 to italic, 3 to bold italic, 4 to symbol. and I don't find how to set plain text. In the following code, the font to use

Thank you for your kind replies. Maybe I was not clear with my question (I apologize) or I did not understand... I would like to take the max for X0...X11 and X12...X24 in my dataset. When I use pmax with the function byapply as in byapply(df, 12, pmax) I get back a list which I cannot convert to a dataframe. Am I missing something? Thanks again! Sincerely, Milu

Hi group, I found a module for adaptive kernel density estimation for Stata users, but unfortunetly I don't have access to Stata, can I find a similar approach using R? Thank u so much 4 ur time. [[alternative HTML version deleted]]

Hi there, In SPSS, small piece of data can be input as following: DATA LIST LIST /x1 x2 x3 x4 x5 . BEGIN DATA 5700 12.8 2500 270 25000 1000 10.9 600 10 10000 3400 8.8 1000 10 9000 3800 13.6 1700 140 25000 4000 12.8 1600 140 25000 8200 8.3 2600 60 12000 1200 11.4 400 10 16000 9100 11.5 3300 60 14000 9900 12.5 3400 180 18000 9600 13.7 3600 390 25000

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Hi there, I hope to draw a plot like this: http://www.sg-chem.net/swizard/Ru-bqdi-spectra.gif is it possible to draw it using R? thanks for any suggestions. regards, Jinsong

Hi, Is there a package that could do response surface analysis equivalent to SAS RSREG procedure? Thanks! Regards, Jinsong

Hi, I hope to use R to perform some hypothesis testing, such as t.test() and var.test(). However, I don't find a function that could do test on means with variance known (i.e., u test or z test in some textbook), and a function that could do test on variances of normal distribution (i.e. chi-squared test). Thanks in advance for any hints. Best wishes, Jinsong

Hi R users, Is is possible for me to use the try function with boot? I would to do the bootstraping with a nonlinear model(it works well when R < 1000). But it does not work very well (when R is large) thus I try to use "try" to resolve. I put the try function in two cases: case1: put the try in front of the boot > c1.try<-try(boot(c1data, statistic = c1.fun,

Dear R-community, I'm analysing some noise using the nlme-package. I'm writing in order to get my usage of lme verified. In practise, a number of samples have been processed by a machine measuring the same signal at four different channels. I want to model the noise. I have taken the noise (the signal is from position 1 to 3500, and after that there is only noise). My data looks like

Dear all, I have a very simple set of data and I would like to analyze them with probit analysis. dose event trial 0.0 3 15 1.1 4 15 1.3 4 15 2.0 3 15 2.2 5 15 2.8 4 15 3.7 5 15 3.9 9 15 4.4 8 15 4.8 11 15 5.9 12 15 6.8 13 15 The dose should be transformed with log10(). I use glm(y ~ log10(dose), family=binomial(link=probit)) to do probit analysis, however, I have to exclude the