similar to: Create a new Vector based on two columns

Hello, I am trying to get a new vector 'x1' based on the not NA-values in column 'a' and 'b'. I found a way but I am sure this is not the best solution. So any ideas on how to "optimize" this would be great! m <- factor(c("a1", "a1", "a2", "b1", "b2", "b3", "d1", "d1"), ordered

Hi, I have a three dimensional array, e.g., my.array = array(0, dim=c(2,3,4), dimnames=list( d1=c("A1","A2"), d2=c("B1","B2","B3"), d3=c("C1","C2","C3","C4")) ) what I would like to get is then a dataframe: d1 d2 d3 value A1 B1 C1 0 A2 B1 C1 0 . . . A2 B3 C4 0 I'm sure there is one function to do

Dear list, I'm trying to add a new dim to a multidimensional array. My array looks like this a1 <- array(1:8, c(2, 2, 2)) dimnames(a1) <- list(A = c("A1", "A2"), B = c("B1", "B2"), D = c("D1", "D2")) I would like to add a new dim 'group' with the value "low".

Dear all: I have this: A1 B1 C1 D1 E1 A2 B2 C2 D2 E2 A3 B3 C3 D3 E3 And I want this A1 E1 B1 E1 C1 E1 D1 E1 A2 E2 B2 E2 C2 E2 D2 E2 A3 E3 B3 E3 C3 E3 D3 E3 Example: m<- matrix(1:15,nrow=3,byrow=T) m v<- unlist(list(t(m[,1:4]))) u<- rep(c(5,10,15),c(4,4,4)) data.frame(v,u) This is the result I want but I would like to learn a simpler way to do it. Any clue?

#I have a data set that looks like this. A bit more complicated actually with # three factor levels but these calculations need to be done on one factor at a #I then have a set of different rates that are applied #to it. #dataset cata <- c( 1,1,6,1,1,2) catb <- c( 1,2,3,4,5,6) doga <- c(3,5,3,6,4, 0) data1 <- data.frame(cata, catb, doga) rm(cata,catb,doga) data1 # start rates #

See if the following helps: > m <- outer(letters[1:5], 1:4, paste, sep="") > m [,1] [,2] [,3] [,4] [1,] "a1" "a2" "a3" "a4" [2,] "b1" "b2" "b3" "b4" [3,] "c1" "c2" "c3" "c4" [4,] "d1" "d2" "d3" "d4" [5,]

Hello all, I have a matrix whose column names look like a1 a2 b1 b2 b3 c1 c2 1 2 3 7 1 3 2 4 6 7 8 1 4 3 Now, I can have any number of a's. not just two as shown above and same goes for b's and c's. I need to extract all the a's columns and put them in another matrix, extract all b's columns and put them in some matrix

Hi, Suppose, if I create 15 files in my working directory. set.seed(48) lapply(1:15,function(i) {m1 <- matrix(sample(1:20,1686*2,replace=TRUE),nrow=1686,ncol=2); write.table(m1,paste0("file_",i,".txt"),row.names=FALSE,quote=FALSE)}) ?D <-dir() D1 <- D[order(as.numeric(gsub("\\D+","",D)))] D1 ?res <- t(sapply(D1,function(x) {x1<-

Dear All, Here is a hypothetical sample (sorry for the clumsy code): A1 <- matrix(1:5, nrow=5, ncol=1) A2 <- matrix(6:10, nrow=5, ncol=1) A3 <- matrix(11:15, nrow=5, ncol=1) A4 <- matrix(16:20, nrow=5, ncol=1) A5 <- matrix(21:25, nrow=5, ncol=1) A6 <- matrix(26:30, nrow=5, ncol=1) B1 <- matrix(c(A1, A2, A3), nrow=5, ncol=3) B2 <- matrix(c(A2, A3, A4), nrow=5, ncol=3) B3

Dear all:   I have this:  A1 B1 C1 D1 E1 A2 B2 C2 D2 E2 A3 B3 C3 D3 E3   And I want this A1 E1 B1 E1 C1 E1 D1 E1 A2 E2 B2 E2 C2 E2 D2 E2 A3 E3 B3 E3 C3 E3 D3 E3   Example:   m<- matrix(1:15,nrow=3,byrow=T) m v<- unlist(list(t(m[,1:4]))) u<-

Greetings, I've been struggling for some time with a problem concerning a big database that i have to deal with. I'll try to exemplify my problem since the database is really big. Suppose I have the following data: AA = c(4,4,4,2,2,6,8,9) A1 = c(3,3,5,5,5,7,11,12) A2 = c(3,3,5,5,5,7,11,12) A = cbind(A, A1, A2) BB = c(2,2,4,6,6) B1 =c(5,11,7,13,NA) B2 =c(3,12,11,NA,NA) B3

With the following example using contr.sum for both factors, > dd <- data.frame(a = gl(3,4), b = gl(4,1,12)) # balanced 2-way > model.matrix(~ a * b, dd, contrasts = list(a="contr.sum", b="contr.sum")) (Intercept) a1 a2 b1 b2 b3 a1:b1 a2:b1 a1:b2 a2:b2 a1:b3 a2:b3 1 1 1 0 1 0 0 1 0 0 0 0 0 2 1 1 0 0 1 0

Dear R users, Basically, from the following arbitrary data set: a <- data.frame(id=c(c("A1","A2","A3","A4","A5"),c("A3","A2","A3","A4","A5")),loc=c("B1","B2","B3","B4","B5"),clm=c(rep(("General"),6),rep("Life",4))) > a

Dear R users: I have some difficulties analizing data with mixed effects NLME and the last version of R. More concretely, I have a repeated measures design with a single group and 2 experimental factors (say A and B) and my interest is to compare additive and nonadditive models. suj rv A B 1 s1 4 a1 b1 2 s1 5 a1 b2 3 s1 7 a1 b3 4 s1 1 a2

I would like to code the following in R: a1(b1+b2+b3) + a2(b1+b3+b4) + a3(b1+b2+b4) + a4(b1+b2+b3) or in summation notation: sum_{i=1, j\neq i}^{4} a_i * b_i I realise this is the same as: sum_{i=1, j=1}^{4} a_i * b_i - sum_{i=j} a_i * b_i would appreciate some help. Thank you. -- View this message in context: http://r.789695.n4.nabble.com/summation-coding-tp4646678.html Sent from the R

I have huge list of edges with weights. a1 b1 w1 a2 b2 w2 a3 b3 w3 a1 b1 w4 a3 b1 w5 I have to convert it into 2 dim matrix b1 b2 b3 a1 max(w1,w4) 0 0 a2 0 w2 0 a3 w5 0 w3 if edges repeated take the maximum weights. How do this efficiently without using for loop? Any idea. thanks Avi [[alternative

I have a dataset that is basically structureless. Its dimension varies from row to row and sep(s) are a mixture of tab and semi colon (;) and example is HEADER1 HEADER2 HEADER3 HEADER3 A1 B1 C1 X11;X12;X13 A2 B2 C2 X21;X22;X23;X24;X25 A3 B3 C3 A4 B4 C4 X41;X42;X43 A5 B5 C5 X51 etc., say. Note that a blank

Dear R people, I have a matrix like this: var1 var2 var3 var4 a1 7.1 7.2 8.1 8.2 a2 10.5 10.6 ... ... a3 b1 b2 b3 b4 c1 c2 ... The matrix row names are "a1", "a2", ...... and the matrix column names are "var1", "var2", "var3" and "var4". Now I want to reshape this data into a

Dear list, I have a list of matrices : i1 <- matrix(1:10, nrow = 2, ncol = 5) i2 <- matrix(11:20, nrow = 2, ncol = 5) j <- list(i1 = i1, i2 = i2) I would like to attribute names to each dimension, for each matrix, as follows : $i1 B1 B2 B3 B4 B5 A1 1 3 5 7 9 A2 2 4 6 8 10 $i2 B1 B2 B3 B4 B5 A1 11 13 15 17 19 A2 12 14 16 18 20 However, I have to use lapply function and attribute

Hi, I am trying to aggregate the sum of my test data.frame as follow: testDF <- data.frame(v1 = c("a", "a", "a", "a", "a", "b", "b", "b", "b", "b", "c", "c", "c", "c", "c", "d", "d", "d", "d",