similar to: Static and dynamic graphics course, July 2007, Salt Lake City

We're pleased to announce a one day course covering static and dynamic graphics using R, ggplot and GGobi. The course will be held just before the JSM, on Saturday, 28 July 2007, in Salt Lake City. The course will be presented by Dianne Cook and Hadley Wickham. In the course you will learn: * How to build presentation quality static graphics using the R package, ggplot. We will cover plot

Hi everyone, We're very pleased to offer a two-day looking-at-data course. July 30-31 Washington DC Day one: static graphics with ggplot2 Day two: interactive graphics with rggobi and GGobi. You can attend one day (for $295) or both days (for $550). Student discounts are available. All proceeds go to the GGobi Foundation to support graphics research. Find out more, and book your tickets

Hi everyone, On Monday, November 14, 2016 the LLVM in HPC workshop will be held in Salt Lake City, Utah (in conjunction with the SC16 conference). For last year's workshop, which was in Austin, we held an LLVM social the evening of the workshop, and I think that turned out really well. If you'll be in Salt Lake City and are interested in attending an LLVM social on the evening of November

We've added 2 additional courses to our April Schedule: (++) R/S Fundamentals and Programming Techniques *** San Francisco / April 24-25, 2008 *** *** New York City / April 28-29, 2008 *** *** Seattle / April 21-22 Regards - Sue > -------- Original Message -------- > Subject: [BioC] XLSolutions 9 Courses: Upcoming March-April 2008 R/S+ > Course Schedule by XLSolutions

Our June-July 2008 R/S+ course schedule is now available. Please check out this link for additional information and direct enquiries to Sue Turner sue at xlsolutions-corp.com Phone: 206 686 1578 Can't see your city? Please email us! www.xlsolutions-corp.com/courselist.htm (1) R/S System: Advanced Programming *** San Francisco / July 28-29, 2008 *** *** Seattle / July 28-29, 2008

X is a matrix and F is a vector. F2 <- data.frame(cbind(X,F)) F2 V1 V2 V3 F 1 -0.250536332 -1.4755883 1.9580974 -2.136487 2 -0.009856084 0.4953269 0.5486092 -2.744482 3 -0.406962682 0.7729631 0.1861905 -2.891821 4 1.938780097 0.7469251 1.2537781 -1.212992 5 -0.332370358 1.1943637 0.7114278 -1.830441 modF<-formula(F ~ V1 + V2 + V3) #no error message

Hi I am looking for a function which is executing some code repeatedly, exactly like lapply() and sappl() are doing, but do not return anything as I am not interested in the return values. An example would be: > p <- data.frame(runif(10), runif(10), runif(10)) > lapply( p, function(ps) {x11(); plot(ps)} ) which results in three graphs and a printout: $runif.10. NULL $runif.10..1

Hi, I'm having trouble with the "which" or the "seq" function, I'm not sure. Here's an example : > lat=seq(1,2,by=0.1) > lat [1] 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 > which(lat==1) [1] 1 > which(lat==1.1) [1] 2 > which(lat==1.2) [1] 3 > which(lat==1.3) [1] 4 > which(lat==1.4) [1] 5 > which(lat==1.5) [1] 6 >

Hi R, Getting a strange result using ?apply. Please look into the below codes: > d=data.frame(a=c(1,2,3),b=c("A","B","C"),c=c(TRUE,FALSE,FALSE),d=c(T,F,F )) > class(d[,1]) [1] "numeric" > class(d[,2]) [1] "factor" > class(d[,3]) [1] "logical" > class(d[,4]) [1] "logical" >

Hi, I tried several settings by using the "family=gaussian" in "gl1ce", but none of them works. For the case "glm" can work. Here is the error message I got: > glm(Petal.Width~Sepal.Length+Sepal.Width+Petal.Length ,data=iris,family=gaussian()) > gl1ce(Petal.Width~Sepal.Length+Sepal.Width+Petal.Length ,data=iris,family=gaussian()) Error in eval(expr, envir,

Hello, I have a loop with probability computed from a logistic model like this: for (i in 1:300){ p[i]<-exp(-0.834+0.002*x[i]+0.023*z[i])/(1+exp(-0.834+0.002*x[i]+0.023 +z[i])) x and z generated from normal distribution. I get 300 different probabilities And I want to generate variables from bernulli distribution with P for every observation: T[i]<-rbinom(1,1,p[i]) But i get missing

I want to extra the part of the formula not including the response variable from an lm object. For example if the lm object ABx.lm was created by the call ABx.lm <- lm( y ~ A + B + x, ...) Then ACx.lm is saved as part of a workspace. I wish to extract "~ A + B + x". Later in my code I will fit another linear model of the form z ~ A + B + x for some other response variable z. I

Hello there, I got a small problem about logical calculation: we can get a sequene from a+b as below: > a<-c(1,2) > b<-c(3,4) > a+b [1] 4 6 but when the sequences are logical. (I want to get (True,False) && (True, True) ==> (True, False), but when I do as below. > e<-c(T,T) > f<-c(F,T) > e [1] TRUE TRUE > f [1] FALSE TRUE >

Dear R Users, I implemented a try() statement that looks like: <- function(index) { reduced_model <- try(glm.fit(X4,n,family=poisson(link="log"))) full_model <- try(glm.fit(X5,n,family=poisson(link="log"))) if (inherits(reduced_model,"try-error") || inherits(full_model,"try-error")) return(NA) else { p <-

Dear all: Assume I have 3 distributions, x1, x2, and x3. x1 ~ normal(mu1, sd1) x2 ~ normal(mu2, sd2) x3 ~ normal(mu3, sd3) y1 = x1 + x2 y2 = x1 + x3 Now that the data I can observed is only y1 and y2. It is easy to estimate (mu1+m2), (mu1+mu3), (sd1^2+sd2^2) and (sd1^2+sd3^2) by EM algorithm since y1 ~ normal(mu1+mu2, sqrt(sd1^2+sd2^2)) and y2 ~ normal(mu1+mu3, sqrt(sd1^2+sd3^2)) However, I want

Hey, all. I had a quick question about fitting new glm values and then looking at the error around them. I'm working with a glm using a Gamma distribution and a log link with two types of treatments. However, when I then look at the predicted values for each category, I find for the one that is close to 0, the error (using se.fit=T with predicted) actually makes it overlap 0.

dear R graphics experts---if anyone is running the combination of R 2.7.0 and ghostscript (2.62), could you please run the following and let me know if you get the same strange symbol size that I do, or if there is something weird on my system? regards, /ivo pdf(file = "testhere.PDF", version="1.4", pointsize=14); plot(0, xlim=c(0,26), ylim=c(-1,4.5), type="n"

rlnorm takes two 'shaping' parameters: meanlog and sdlog. meanlog would appear from the documentation to be the log of the mean. eg if the desired mean is 1 then meanlog=0. So to generate random values that fit a lognormal distribution I would do this: rlnorm(N , meanlog = log(mean) , sdlog = log(sd)) But when I check the mean I don't get it when sdlog>0. Interestingly I

Hi. Here are three successive examples of simple quadratic programming problems with the same structure. Each problem has 2*N variables, and should have a solution of the form (1/N,0,1/N,0,...,1/N,0). In these cases, N=4,5,6. As you will see, the N=4 and 6 cases give the expected solution, but the N=5 case breaks down. >cm8 [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [1,] 1 0

Hi R, I have a list of matrices. I need to get the sum of all the matrices in the list. Example: a=b=c=d=matrix(1:4,2,2) l=list(a,b,c,d) I need: > a+b+c+d [,1] [,2] [1,] 4 12 [2,] 8 16 Something like do.call("+",l) is not working...why is this? I may not be knowing the number of matrices in the list... Thanks, Shubha This e-mail