similar to: Potential problem with tapply

Dear List, why does this not work? df <- data.frame(var1 = c(3,2,1), var2 = c(6,5,4), var3 = c(9,8,7), fac = c('A', 'A', 'B')) tapply(cbind(df$var1, df$var2, df$var3), df$fac, mean) Thank you, Stefan

Is the following behaviour of the quantile function what one would expect? > a <- 1:100 > quantile(a,.6) 60% 60.4 Philippe -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the

Just a word to mention that I have lost 2 hours yesterday to find out why R refused to use a function from a package calling C-code. R invariably answered that the C code was not in the load table (something like this). I have tried everything (or nearly) to solve my problem knowing that this same package used to work on my computer at the university. Finally, I found out that running the same

I can't quite seem to solve a problem subsetting a data frame. Here's a reproducible example. Given a data frame: dat <- data.frame(fac = rep(c("a", "b"), each = 100), value = c(rnorm(130), rep(NA, 70)), other = rnorm(200)) What I want is a new data frame (with the same columns as dat) excluding the top 5% of "value"

Hi, I've been passing the hist() function to tapply() to quickly generate histograms based on the list of factors supplied to tapply(). However, I have not figured out how to generate titles for each of the histograms, which paste in the unique values of the list factors as part of the histogram title. I'm hoping that someone can tell me how to do this. Thanks for your time and

I was using R 1.5.1 today with an old script from S-Plus and discovered that R does not have reorder.factor. It's a very simple function, but very handy for re-arranging factors in lattice graphics (among other places). Would it make sense to add this function to the base code in order to increase compatability with S-Plus and add additional functionality? reorder.factor <-

This one should be easy but it's giving me a hard time mostly because tapply puts the results in a list. I want to calculate the cumulative sum of a variable in a dataframe, but with the accumulation only within each level of a factor. For a very simple example, take: > df <- data.frame(x=c(rep(1,5),rep(2,5),rep(3,5)),fac=gl(3,5,labels=letters[1:3])) > df x fac 1 1 a 2 1 a

mingw, llvm 2.6 (buid with llvm-gcc) Example source code: http://npcontemplation.blogspot.com/2008/06/secret-of-llvm-c-bindings.html I change LLVMCreateJITCompiler(&engine, provider, &error); to LLVMCreateJITCompiler(&engine, provider, 3, &error); $ llvm-gcc `llvm-config --cflags` -c fac.c $ g++ `llvm-config --libs --cflags --ldflags core analysis executionengine jit

Hi, I am analyzing a data set with greater than 1000 independent cases (collected in an unrestricted manner), where each case has 3 variables associated with it: one, a factor variable with 0/1 levels (called XX), another factor variable with 8 levels (X) and a third response variable with two levels (Y: 0/1). I am trying to see if X1 has an effect on the relationship between X2 and the

Hi, I need to resample rows in a data frame by subsets L3 <- LETTERS[1:3] d <- data.frame(cbind(x=1, y=1:10), fac=sample(L3, 10, repl=TRUE)) x y fac 1 1 1 A 2 1 2 A 3 1 3 A 4 1 4 A 5 1 5 C 6 1 6 C 7 1 7 B 8 1 8 A 9 1 9 C 10 1 10 A I have seen this used to sample rows with replacement d[sample(nrow(d), replace=T), ] x y fac 7 1 7 B 2

Dear all, I'm using the mgcv library by Simon Wood to fit gam models with interactions and I have been reading (and running) the "factor 'by' variable example" given on the gam.models help page (see below, output from the two first models b, and b1). The example explains that both b and b1 fits are similar: "note that the preceding fit (here b) is the same as

Dear list, I'm trying to create a matrix by combining the sites that species occur in a new matrix with species as rows and sites as columns. The main matrix is "mat": mat <- as.data.frame(cbind(sp1=c(rep(0, 5), rep(1, 5)),sp2=sample(c(rep(0, 6),rep(1, 4))), fac=c(rep("a", 3), rep("b", 3),rep("c", 4)))) The first two columns are species and the

Hi all, I noticed something strange when I ran aov and anova. vtot=c(7.29917, 7.29917, 7.29917) #identical values fac=as.factor(c(1,1,2)) #group 1 has first two elements, group 2 has the 3rd element When I run: > anova(lm(vtot~fac)) Analysis of Variance Table Response: vtot Df Sum Sq Mean Sq F value Pr(>F) fac 1 1.6818e-30 1.6818e-30 0.3333 0.6667 Residuals 1

Suppose I have a dataframe 'd' defined as L3 <- LETTERS[1:3] d0 <- data.frame(cbind(x = 1, y = 1:10), fac = sample(L3, 10, replace = TRUE)) (d <- d0[d0$fac %in% c('A', 'B'),]) x y fac 2 1 2 B 3 1 3 A 4 1 4 A 5 1 5 A 6 1 6 B 8 1 8 A Even though factor 'fac' in 'd' only has 2 levels, but it seems to bear the birthmark

[I originally posted this on the R-help mailing list, and it was suggested that R-devel would be a better place to dicuss it.] Running ?table? on a factor with levels containing non-ASCII characters seems to result in extremely bad performance on Windows. Here?s a simple example with benchmark results (I?ve reduced the number of replications to make the function finish within reasonable time):

Hi, I am trying to plot an interaction.plot with different color for each level of a factor. It has an erratic behavior. For example, it works for the first interaction.plot below, with the example from the ALDA book, but not with the other plots, from the NPK dataset: # from http://www.ats.ucla.edu/stat/r/examples/alda/ch2.htm tolerance <-

Hi I'm doing a glm analysis and I have two doubts (at least :) 1) When I run the function it gives a lot of warnings (see below) what they mean ? (may be I'm ignorant about this analysis ...) glm.poisson<-glm(log(Jkij+1)~fac.ano+fac.tri+fac.icesr+fac.mat+fac.ano:fac.icesr+fac.ano:fac.tri,family=poisson()) warnings() 40: non-integer x = 1.252763 41: non-integer x = 1.864785 42:

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Hi all, I had some trouble in?regrouping factor levels for a variable. After some experiments, I have figured out how I can recode to modify the factor levels. I would now like some help to understand why some methods work and others don't. Here's my code : rm(list=ls()) ###some trials in recoding factor levels char<-letters[1:10] fac<-factor(char) levels(fac) print(fac) ##first

hi ,everyone I want subtract some dataset by subset. >From the help running help(subset), ths information is "*subset(airquality, Day == 1, select = -Temp)* " while I running my script written as "*g1data<-subset(errdata, fac>12) *" ,it is wrong with the error information "*subset.default(newerrdata, fac>12),can not find fac*" and g1 in read