similar to: Tukey's one degree of freedom for nonadditivity?

Hello, I have a dataframe of say 20 lines with one line per individual. I want to group these 20 individuals by length class (eg. of 5cm) and get the mean value of all the other variables (eg VarA and VarB) for each length class My dataframe is as follow: Length <- 10:30 VarA <- seq(1000,1200,10) VarB <- seq(500,700,10) Data <- cbind(Length,VarA,VarB) And I want to get something

Hello,   I'd like to generate automatically all the possible combinations of a set of 8 variables (there are 535, too many to do it by hand). For example:   input: varA, varB, varC output: varA+varB+varC             varA+varB             varA+varC             varB+varC             varA             varB             varC Is there any function that produces this option?   Thank you [[alternative

Hi, I wonder whether the following is possible with R, and whether anyone has done that and can share his/her code with me. I have a correlation matrix, and I want to create a correlation table that I can copy to Microsoft Word with a superscript above each correlation, indicating significant differences in the same row. That is, when correlations in the same row do not share superscript, it means

Hi: Can anyone advice me on how to loop and perform a calculation through all the columns. here's my data xd<- c(2.2024,2.4216,1.4672,1.4817,1.4957,1.4431,1.5676) pd<- c(0.017046,0.018504,0.012157,0.012253,0.012348,0.011997,0.012825) td<- c(160524,163565,143973,111956,89677,95269,81558) mydf<-data.frame(xd,pd,td) trans<-t(mydf) trans I have these values that I need to

Hello, I have some code that currently works fine and I am endeavoring to convert the major pieces of it into functions. This involves taking "hard coded" names of variables that are used in various places and figuring out how to abstract them out into functions where the arguments (i.e. a list of variables)?can be passed to the parent function and used within that function for various

Dear R Users, Am using lm() with contrasts as below. If I skip the contrasts() statement, I get the coefficient names to be > names(results$coef) [1] "(Intercept)" "VarAcat" "VarArat" "VarB" which are much more meaningful than ones based on integers. Can anyone tell me how to get R to keep the coefficient names based on the factor levels

Dear Lister, I understand merge() can be used to join 2 data frames based on 1 variable. But how about merge based on more than 2 variables? Thank you so much! -- WenSui Liu (http://spaces.msn.com/statcompute/blog) Senior Decision Support Analyst Health Policy and Clinical Effectiveness Cincinnati Children Hospital Medical Center [[alternative HTML version deleted]]

Hi, I have a data set that looks like this: > data vara varb S PC 1 None 250 1 80 2 None 250 1 70 3 Some 250 1 60 4 Some 250 1 70 5 None 1000 1 90 6 None 1000 1 90 7 Some 1000 1 80 8 Some 1000 1 70 9 None 250 2 100 10 None 250 2 80 11 Some 250 2 70 12 Some 250 2 70 13 None 1000 2 100 14 None 1000 2 90 15 Some 1000 2 50 16 Some 1000 2 40 ... And so on.

Dear list members, Where can I find code for computing the p*p variance-covariance matrix given a vector of p variances (ordered varA, varB, ..., varp) and a vector of all possible correlations (ordered corAB, corAC, ..., corp-1,p)? I know that the covariance between 2 variables is equal to the product of their correlation and their standard deviations: corAB * varA^.5 * varB^.5 and so:

Dear R users, I'm having a hard time with some very simple things. I have a time series where the dates are in the format 7-Oct-04. I imported the file with read.csv so the date column is a factor. The series is rather long and I want to plot it piece by piece. The function below works fine, except that the labels for date are meaningless (ie 9.47e+08 or 1098000000 - apparently the number of

Let's say I have a program that returns variables whose names may be any string within the vector NAMES=c("varA","varB","varC","varD","varE","varF"..."varZ"), but I do not ever know which ones have actually been created. So in one example output, "varA", "varC", and "varD" could exist, but

Dear R-list, I have a data set (in the following example called "a") which have: one "subject indicator" variable (called "id") three dependent variables (varD, varE, var F) three independent variables (varA, varB, varC) I want to fit 9 lme models, one per posible combination (DA, DB, DC, EA, EB, EC, FA, FB, FC). In stead of writting the 9 lme models, I want to

Hi, I have a 3 panel xyplot with different variables in the y axis. I'm trying to insert a newline after "Width (cm)," in the ylab argument as in the example below. My goal is to have the y axis label broken into two lines, split after the string just mentioned. plotfun <- function() { fakedf <- data.frame(A = sample(1:100, 50), B = rnorm(50),

> Chandler’s complex arithmetic changes are also in the range: r219557 in clang. We saw it change the code in mandel-2 significantly. mandel-2 is broken on hard FP ABI systems, btw. The reason is simply: we're emitting a call to __muldc3 with AAPCS VFP calling convention, however, the function expects softfp (AAPCS) calling conv and reads garbage from GP registers. I'm working on fix.

Hi all, We have 4 outstanding tests on clang-mergefunc-x86_64-freeBSD9.2 builder. I have introduced issues for them in bugzilla: http://llvm.org/bugs/show_bug.cgi?id=18089 http://llvm.org/bugs/show_bug.cgi?id=18056 Since we have opened issues for these tests, can we add them to ignore-list for this builder? It allows faster catch and fix other failures (if we get them). I also wandering, may be

Dear R users, I have some trouble using the allEffects() function to compute and display effect plots for a linear model. My data is quite simple, it concerns effects of 3 treatments on the tumoral volume of mice. vTum codes for the qualitative initial volume, from small to big, temps is the time in month since beginning of treatment, and S?rie codes for the batch. Data is unbalanced. >

Hey everyone, Not sure if anyone had tried this but I managed to get LLVM and clang to build on Nexenta Alpha 7. This is an OpenSolaris/GNU OS. There wasn't much to change for LLVM, except "#undef"ing a lot of x86 register name equivalents and the like (ie. EAX,ESP,CS,FS...). There were a couple of similar undef's needed for clang, as well. The clang testsuite ran fine except

Dear Colleagues, John Mandel ( Chain block designs with two-way elimination of heterogeneity. Biometrics 10, 251-272 ,1954). extended the class of chain block designs (Youden & Conner (1953) to elimination of both row and column (blocks) effects. These experimental designs can be useful in engineering and other fields. I am having difficulty obtaining his adjusted treatment means in his

Hi Chandler, That's embarrassing how weird this part of clang is. I have a provisional patch which fixes the problem but underlines clang's problems. I will submit it tonight for comments. суббота, 18 октября 2014 г. пользователь Chandler Carruth написал: > > On Fri, Oct 17, 2014 at 7:51 AM, Anton Korobeynikov < > anton at korobeynikov.info >

Folks, First win of the benchmark buildbot! http://llvm.org/perf/db_default/v4/nts/graph?plot.0=49.128.2&highlight_run=31861 It seems mandel-2 had a huge regression a few commits ago, and based on a quick look, it may have to do with the inst combine changes. I haven't investigated yet, but this is the first time I spot regressions on test-suite, so I'd like to first congratulate