similar to: tip: large plots

Ok, so I'm slowly figuring out what a factor is, and was able to follow the related thread about finding a mode by using constructs like my_mode = as.numeric(names(table(x))[which.max(table(x))]) Now, suppose I want to keep looking for other modes? For example, Rgames> sample(seq(1,10),50,replace=TRUE)->bag Rgames> bag [1] 2 8 8 10 7 3 2 9 8 3 8 9 6 6 10 10 7 1

"Not that it really matters, but" Can someone explain how the row numbers get assigned in the following sequence? It looks like something funky happens when rbind() coerces 'bar' into a dataframe. In either sequence of rbind below, once you get past the first two rows, the row numbers count normally. Rgames> (foo<-data.frame(x=5,y=4,r=3)) x y r 1 5 4 3 Rgames>

I feel bad even asking, but: Rgames> data(OrchardSprays) Rgames> model<-lm(decrease~.,data=OrchardSprays) Rgames> model Call: lm(formula = decrease ~ ., data = OrchardSprays) Coefficients: (Intercept) rowpos colpos treatmentB treatmentC 22.705 -2.784 -1.234 3.000 20.625 treatmentD treatmentE treatmentF treatmentG treatmentH

Dear list, I have been struggling for some time now with this code... I have this vector of unique ID "EID" of length 821 extracted from one of my dataframe (skate). It looks like this: > head(skate$EID) [1] "896-19" "895-8" "899-1" "899-5" "899-8" "895-7" I would like to remove the complete rows in another dataframe

Hello, everybody! I have a matrix "input" (see example below) - with all unique entries that are actually unique ranks (i.e., start with 1, no ties). I want to assign a value of 100 to the first row of the column that contains the minimum (i.e., value of 1). Then, I want to assign a value of 100 to the second row of the column that contains the value of 2, etc. The results I am looking

Hi, Here's the problem I ran into: the gmp package has a method for apply() so it masks the base::apply function. With gmp installed, I tried to run the function turnpoints() from the pastecs package. It fails because it calls apply() internally, like this: apply(mymatrix,1,max,na.rm=TRUE) , but the code in the gmp package which sets up the operator overload for apply() strictly

Dear R users, I'd like to count the number of integers in a vector y. Here is an example. y <- c(0,1,1,3,3,3,5,5,6) In fact, I know how to count the number of specific number in y. sum(y==0) -> 1 sum(y==1) -> 2 sum(y==2) -> 0 sum(y==3) -> 3 sum(y==4) -> 0 sum(y==5) -> 2 sum(y==6) -> 1 However, in one computation I want to get this vector [1,2,0,3,0,2,1]. Thank

Hey All, You know how sometimes you have a problem but you just live with it? Well I've got one of those problems. I have an HP-2025dn printer connected to my home network. When I print a plain text document containing the text, "this is a test", from my wife's Windows 7 machine using the text editor the print job finishes in less than 15 seconds. If I print two copies the

I have found following problem: I have a vector: > a <- c(1.04,1.04,1.05,1.04,1.04) I want a mean of this vector: > mean(a) [1] 1.042 which is correct, but: > mean(1.04,1.04,1.05,1.04,1.04) [1] 1.04 gives an incorrect value. how is this possible? thanks, zbynek -- View this message in context: http://r.789695.n4.nabble.com/Incorrectness-of-mean-tp3327701p3327701.html Sent from the R

Hi all, I have a set of data in hourly time steps with each row identified as time data column1 data column2 1 9999 9999 1.042 9999 9999 1.083 9999 9999 1.125 9999 9999 1.167 9999

Hello, I do not have any statistical background, So I shall apologise if I am asking trivial question or help. I am trying to work with R. The problem I have on hand is: I have 2 sets of data(means & SD for each sample in the group of both sets). The sample size is massive(2000+ in each grp). I have a new set of experimental data and I like to classify this to either of the grps based on

I've been doing some consulting with students who seem to come to R from SAS. They are usually pre-occupied with do loops and it is tough to persuade them to trust R lists rather than keeping 100s of named matrices floating around. Often it happens that there is a list with lots of matrices or data frames in it and we need to "stack those together". I thought it would be a simple

First - many, many congrats to team ZFS. Developing/writing a new Unix fs is a very non-trivial exercise with zero tolerance for developer bugs. I just loaded build 27a on a w1100z with a single AMD 150 CPU (2Gb RAM) and a single (for now) SCSI disk drive: FUJITSU MAP3367NP (Revision: 0108) hooked up to the built-in SCSI controller (the only device on the SCSI bus). My initial ZFS test was to

Hi, I'm very new to working with sparse matrices and would like to know how I can column permute a sparse matrix. Here is a small example: > M1 <- > spMatrix(nrow=5,ncol=6,i=sample(5,15,replace=TRUE),j=sample(6,15,replace=TRUE),x=round_any(rnorm(15,2),0.001)) > M1 5 x 6 sparse Matrix of class "dgTMatrix" [1,] 2.983 . 1.656 5.003 . . [2,] .

With rw2010dev I get a strange protect(): protection stack overflow error with a small data frame which otherwise is usable: If anybody wants to have a look I can provide an RData file with the problematic data frame. Doesn't seem to be necessary, the following simulated example generates the error: > testmat <- matrix(1:80, 20,4) > dim(testmat) [1] 20 4 > str(testmat) int

Hello, my test.R file contains two huge arrays (>3000 entries), from which R needs to calculate the Pearson Correlation, if I look at the file the numbers look correct. if I run R R < test.R --no-save I see things like this: 0.723, 0.838, 1.002, 0.364, 0.357, 0.227, 0.982+ , 0.963, 0.535, 1.214, 1.270, 0.832, 1.033, 0.632, 2.482, 1.239, 0.743, 1.077, 0.962, 1.052, 1.075, 1.427, 1.395,

I really would like to be able to read about this in a document but I cannot find my way around the documentation properly Given the code... M <- matrix(runif(5*20), nrow=20) colnames(M) <- c('a', 'b', 'c', 'd', 'e') ind <- c(1,2,3,4) dep <- 5 I can then do... l2 <- lm(M[,dep]~M[,ind]) ## Clearly not useful! summary(l2) I am not sure what

Hello all! I have a problem to arrange data in another form. My initial data is like this: 'data.frame': 421 obs. of 58 variables: $ 01A: num NA NA NA NA NA NA NA NA NA NA ... $ 01B: num NA NA NA NA NA NA NA NA NA NA ... $ 03A: num NA NA NA NA NA NA NA NA NA NA ... $ 03B: num NA NA NA NA NA NA NA NA NA NA ... $ 05A: num NA NA NA NA NA NA NA NA NA NA ... $ 05B: num NA NA NA NA

Hello R users, For the last few days I am struggling with the following task: my data.frame: A1 A2 A3 B1 B2 B3 58.81 53.292 54.501 13.013 17.39 19.407 56.02 56.251 54.033 20.099 13.15 10.411 55.376 53.099 57.625 13.396 21.031 13.22 58.584 53.194 54.218 13.038 16.854 19.289 55.7 55.921 53.847 19.942 13.153 9.828 55.093 52.934

Dear ReXperts, I have the below text file output. I need to extract the T, QC, QO, QO-QC and WT columns for the data between T = 10 and T=150. Any ideas? Thanks in advance. ======================================================================================== 1 D C ---CAT-- T THETA QC QO QO-QC QC/QO WT FSD 8 1 0 1.0000E+01