similar to: sapply behavior

Hi, I am using eigen to get an eigen decomposition of a square, symmetric matrix. For some reason, I am getting a column in my eigen vectors (the 52nd column out of 601) that is a column of all NAs. I am using the option, symmetric=T for eigen. I just discovered that I do not get this behavior when I use the option EISPACK=T. With EISPACK=T, the 52nd eigenvector is (up to rounding error) a

Hi, When I go to the CRAN page to download a new version of R, there are not the same versions available depending on which mirror I pick. When I go to http://cran.cnr.berkeley.edu/, for example, I get 2.2.1, but if I go http://cran.stat.ucla.edu/ the option is 2.2.0 (I'm downloading the Windows base file). Neither refreshing nor clearing my cache changes it. For future reference, I'd

Hello. I am wondering why I am getting NA for all in cors=sapply(pred,cor,y=resp). I suppose that each column in pred has NAs in them. Is there some way to fix this? Thanks > str(pred) 'data.frame':   200 obs. of  13 variables:  $ mnO2: num  9.8 8 11.4 4.8 9 13.1 10.3 10.6 3.4 9.9 ...  $ Cl  : num  60.8 57.8 40 77.4 55.4 ...  $ NO3 : num  6.24 1.29 5.33 2.3 10.42 ...  $ NH4 : num  578

Hello, I came across the following behavior, which seems illogical to me. I don't know if it is a bug or if I'm missing something: > all(logical(0)) [1] TRUE > any(logical(0)) [1] FALSE > isTRUE(logical(0)) [1] FALSE This actually came up in practice when I did something like > all( names(x) %in% vec ) as an error-handling, and I was hoping that it would work regardless

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 User, thank for the attention. I have a data.frame with 5 columns (ex:ID, a1,a2,a3,a4) and 1000 rows. I wish to find the absolute max value for all data.frame and save a new data.frame with the row where is that value. Ex: ID: 1,2,3,4,5,6,7,8,9,10 a1:1,2,3,4,5,6,7,8,9,10 a2:11,12,13,14,15,16,17,18,19,20 a3:21,22,23,24,25,26,27,28,29,30 a4:31,32,33,34,35,36,37,38,39,40 The

Hello, I'm new in R and I want to do one thing that is very easy in excel, however, I cant do it in R. Suppose we have the data frame: data<- data.frame(A=c("a1","a2","a3","a4","a5")) I need to obtain another column in the same data frame (lets say B=c(b1,b2,b3,b4,b5) in the following way: b1=a1/(a1+a2+a3+a4+a5)

Buenas, Tengo dos data.frames de la siguiente manera library(data.table) id<-c("a1","a2","a3","a4") id2<-c("a2","a3","a1","a4") y<-c(1,2,3,4) z<-c(3,5,6,7) k<-c(1,3,8,7) df1<-data.table(id,y,z) id<-c("a2","a3","a1","a4") df2<-data.table(id,x,y) Quiero

Hello, I am running large simulations, which unfortunately I can't really replicate here because the code is so extensive. I rely heavily on mclapply, but I realize that I'm losing data somewhere. There are two worrisome symptoms: 1) I am getting 'NULL' as a return value for some (but not all) elements of the output when I use mclapply, but not if I use lapply > tmp2[1:3]

Hi, I'm trying to conduct sensitivity analysis in R using the 'sensitivity' package. Although the description of functions seem straightforward, I can?t succeed. The definition of input factors can be the problem. library(sensitivity) #A simple model with 4 input factor to test the morris function: model01=function(a1,a2,a3,a4) { Z<-numeric(10) Z[1]<-runif(1)

Dear colleagues, I'd like to reshape a datafame in a long format to a wide format, but I do not quite get what I want. Here is an example of the data I've have (dat): sp <- c("a", "a", "a", "a", "b", "b", "b", "c", "d", "d", "d", "d") tr <- c("A",

I would like to compare two data sets saved as text files (example below) to determine if both sets are identical(or if dat2 is missing information that is included in dat1) and if they are not identical list what information is different between the two sets(ie output "a1", "a3" as the differing information). The overall purpose would be to remove "a1" and

Dear R users, I have a data where I desire to subset according to certain conditions. However, the script is very messy as there are about 30 distinct conditions. (i.e. same script but with different conditions) I would like to make a user defined function so that I can input the desired conditions and just get the results accordingly. Below is an arbitrary data set & sample statements

Full_Name: Elizabeth Purdom Version: 1.9.1 OS: Windows XP Submission from: (NULL) (171.64.102.199) It would be nice if legend had the option of some default locations you could choose instead of entering specific coordinates, like "topleft", "topright","topcenter", etc. based on par("usr") coordinates. I know I've wanted it so often I've made my

I spent a lot of time searching and came up empty handed on the following query. Is there an equivalent to rowSums that does product or cumulative product and avoids use of apply or looping? I found a rowProd in a package but it was a convenience function for apply. As part of a likelihood calculation called from optim, I?m computing products and cumulative products of rows of matrices with

Hi everyone, I have two columns: ? ?A? ? ? ? ? ? ? ?B ? ?1? ? ? ? ? ? ? ?1? ?1? ? ? ? ? ? ? ?0 ? ?0? ? ? ? ? ? ? ?1 ? ?0? ? ? ? ? ? ? ?0 I have 4 categories which are: 1) if A = 1 and B =1 then A1 = 1, else A2 = 0, A3 = 0, A4 = 0 2) if A = 1 and B =0 then A1 = 0, else A2 =1, A3 = 0, A4 = 0 3) if A = 0 and B = 1 then A1 = 0, else A2 = 0, A3 = 1, A4 = 0 4) if A = 0 and B =0 then A1 = 0, else A2 =

Hello I have a data set like below: plate.id well.id Group HYB rlt1 1 P1 A1 Control SKOV3hyb 0.190 2 P1 A2 Control SKOV3hyb 0.210 3 P1 A3 Control SKOV3hyb 0.205 4 P1 A4 Control SKOV3hyb 0.206 5 P1 A5 Control SKOV3hyb 0.184 385 P1 A1 ovca SKOV3hyb 0.184 386 P1 A2 ovca SKOV3hyb 0.229 387

Hi, I want find all roots for the following polynomial : a <- c(-0.07, 0.17); b <- c(1, -4); cc <- matrix(c(0.24, 0.00, -0.08, -0.31), 2); d <- matrix(c(0, 0, -0.13, -0.37), 2); e <- matrix(c(0.2, 0, -0.06, -0.34), 2) A1 <- diag(2) + a %*% t(b) + cc; A2 <- -cc + d; A3 <- -d + e; A4 <- -e fn <- function(z) { y <- diag(2) - A1*z - A2*z^2 - A3*z^3 - A4*z^4

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

I have the following array: 3 dimensional object, one dimension being year. Object is 3*3*3 library(plyr, reshape) a1<-rep(c(2007,2008,2009),9) a2<-c(rep("a",9),rep("b",9),rep("c",9)) a3<-c(rep(c(rep(1,3),rep(2,3),rep(3,3)),3)) a4 <- rnorm(27) A<-data.frame(cbind(comp=a2,val=a3, year=a1, a4)) A1<-melt(A, id=c("year", "comp",