similar to: Create new Vector based on two colums

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".

Hallo HelpeRs, I try to reconstruct some results from an econometric text book (Heij et al. (2004), pp. 218-20). For the data > x <- structure(list(q1 = c(345, 331, 320, 314, 299, 395, 415, 490, 547, 656, 628, 627), d1 = c(1, 1, 1, 1, 1, 1, 1.05, 1.05, 1.05, 1.15, 1.15, 1.15)), .Names = c("q1", "d1"), row.names = as.integer(c(NA, 12)), class =

I have the following: Time A1 A1 B1 B1 C1 C2 x y x y x y 0 5 6 6 7 7 9 1 3 4 4 3 9 9 2 5 2 6 4 7 4 I want to change it to the following: 0 1 2 x y x y x y A1 5 6 3 4 5 2 B1

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 #

Hi... Started playing with gluster. And the heal functions is my "target" for testing. Short description of my test ---------------------------- * 4 replicas on single machine * glusterfs mounted locally * Create file on glusterfs-mounted directory: date >data.txt * Append to file on one of the bricks: hostname >>data.txt * Trigger a self-heal with: stat data.txt =>

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<-

Using S+ 6 for Linux and R 1.4.1 Taking verbatim some lines from S-Plus that work perfectly, and running them on R, I get an unexpected error message: R : Copyright 2002, The R Development Core Team Version 1.4.1 (2002-01-30) > library(MASS) > data <- read.table("/usr/local/data/mcmanus.dat",header=T) > mcmanus.frm <-

Hey all, after installing the 3.0.0 version of puppet (debian package from puppetlabs), doing the initial config, doing an initial start of master to generate the certs needed and then starting apache with passenger to control puppetmaster. I can do: puppet ca list --all and get a listing of the certs in the system (initially only the master). afterwards, on the client node, I run: puppet

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,]

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<-

Hi everyone I am trying to estimate the optimal hedge variance ratio for cross hedging two commodities. the price levels are used (compared to price change and % price change) and used the OLS with dummy variable for estimating the co-efficients. the equation looks like this Y = B + B1*D1 + B2*X + B3*(X*D1) Where Y = Daily Cash market price D1 = Dummy variable taking value 1 for period Oct-Mar

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 R Users Hi, I have very emergency problems in my programming about finding MLE with optim command. I reproduced it with real data. I guess that my function object in optim is very sensitive because it has power function . Then optim give me lower or initial values for estimates with these warnings for Hessian matrix computation: 1: In log(B2 * (C2^(y + v))) : NaNs produced 2: In log(B3

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

I am trying to code the following excel formula in R. a b c Result Formula 1 10 0.1 #N/A IF(B2<20,NA(),C2+IF(ISERROR(D1),0,D1)) 2 20 0.2 0.2 IF(B3<20,NA(),C3+IF(ISERROR(D2),0,D2)) 3 30 0.3 0.5 IF(B4<20,NA(),C4+IF(ISERROR(D3),0,D3)) 4 40

Dear all, I have a big problem: - I got two matrices, A and B - A shows identifies the value of B, however the values of B must be summed - For instance, 1 1 2 2 2 2 1 1 gives matrix a 3 4 2 1 1 1 2 2 gives matrix b Now the result for the value 1 would be 7 4 which are the rowsums of the values of matrix B given that matrix A has the value 1. How can I do this automatically? I

Hi. I have tried to use Package "SEM". As a learning, I try to convert a program running well of EQS which is as follows to SEM: ### EQS ### /SPECIFICATION CAS=100; VAR=5 MAT=COR; ANA=COR; /EQUATIONS V1=*F1+E1; V2=*F1+E2; V3=*F1+*F2+E3; V4=**F1+*F2*E4; V5=*F2+E5; /VAR E1 TO E5=*; F1*1.0; F2=1.0; /COV E1,E2=*; F1,F2=*: /PRINT FIT ALL; /MATRIX ...... /END This is the converted SEM