similar to: match help

I have created a list of "matrices" using sapply or lapply and wish to extract each of the "matrices" as a matrix. Some of them are 2x2, 3x3, etc. I can do this one at a time as: M1<-as.matrix(D[[1]]) How can repeat this process for an unknown number of entries in the list? In other words, how shall I index M1? Diana

X is a matrix and F is a vector. F2 <- data.frame(cbind(X,F)) F2 V1 V2 V3 F 1 -0.250536332 -1.4755883 1.9580974 -2.136487 2 -0.009856084 0.4953269 0.5486092 -2.744482 3 -0.406962682 0.7729631 0.1861905 -2.891821 4 1.938780097 0.7469251 1.2537781 -1.212992 5 -0.332370358 1.1943637 0.7114278 -1.830441 modF<-formula(F ~ V1 + V2 + V3) #no error message

i would like to add a variable to an existing matrix by manipulating 2 previous variables eg for the data m treat strata censti survTime [1,] 1 2 284.684074 690.4961005 [2,] 1 1 172.764515 32.3990335 [3,] 1 1 2393.195400 24.6145279 [4,] 2 1 30.364771 8.0272267 [5,] 1 1 523.182282 554.7659501 l

I use matplot to get the density curve and then I use abline(v=g$V2, col = 3 ) to get the vertical line. Goal : I want very small lines at the bottom on the x axis , if possible in the arrow forms instead of vertical lines on the whole graph. Thanks a lot. [[alternative HTML version deleted]]

Hello R-ologists, Imagine you have a list "list" like so: >list [[1]] [1] "IPI00776145.1" "IPI00776187.1" [[2]] [1] "Something" "IPI00807764.1" "IPI00807887.1" [[3]] [1] "IPI00807764.1" [[4]] [1] "Somethingelse" What I need to achieve is a filtered list "list2" like so: >list2 [[1]] [1]

ng, I have a matrix (x) with binary content. Each row of the matrix holds exactly one 1, and the rest of the row is zeros. The thing is that I need to 'collapse' the matrix to one column where each row holds the original column index of the 1's (y). Sometimes, the matrix is quite large, so I have a perfomance problem. x <- matrix(c(1,0,0, 0,0,1, 0,1,0, 0,0,1, 0,1,0,

Can anyone please tell me if there is a function to calculate confidence intervals for the results of the quantile function. Some of my data is normally distributed but some is also a squewed distribution or a capped normal distribution. Some of the data sets contain about 700 values whereas others are smaller with about 100-150 values, so I would like to see how the confidence intervals change

Dear UseRs, I have a very simple question. I have a big matrix (say x) including probabilities (values in (0,1)). I have to store in a list the names of the row and the column where max(x) is located. How can I proceed? Thanks in advance for your assistance! mirko

Dear All, I couldn't figure and couldn't google out how to make construct a pair of \Sexpr s or a LaTeX macro that would include 5\cdot 10^{-12} into the LaTeX output istead of 5e-12 . Any ideas? Thank you G?bor

Dear all, I'm a newbie to R and I would really apperciate any help with the following: I have two lists, l1 and l2: l1: $"A*0101" [1] 0.076 0.109 0.155 0.077 0.09 0 0 0.073 [9] 0.33 0.0034 0.0053 $"A*0247" [1] 0 0 0.5 .004 0 0 0 $"A*0248" [1] 0 0 0.3 0 0.06 .... l2: $"A*1101" [1] 0.17 0.24 0.097 0.075 0.067 $"A*0247" numeric(0)

I have got a dataframe containing measurement of aircraft noise like this: > Id <- c(1,4,5,2,3,6,4,1,2,5,6,3) > Noise <- c(88,94,97,98,92,56,103,102,87,95,92,97) > Height <- c(190, 150, 120, 115, 188, 104, 101, 189, 146, 111, 124, 126) > > df <- data.frame(Id, Noise, Height) Now I would like to split this in two new dataframes. The first one containing the rows

I am struggling with R code optimization, a recurrent topic on this list. I have three arrays, say A, B and C, all having the same number of columns. I need to compute an array D whose generic element is D[i, j, k] <- sum_n A[i, n]*B[j, n]*C[k, n] Cycling over the three indices and subsetting the columns won't do. Is there any way to implement this efficiently in R or should I resign to

Hi I have the following array: test <- array(c(1:16), dim = c(3,4,3)) test ## I call some enries using an index array test.ind <- array(rbind(c(1,2,1), c(3,3,2)), dim = c(2,3)) test[test.ind] ## suppose I want all values in the 2nd row and 4th col over ## all three 3rd dimensions test[2,4,] how to specify a test.ind array with the last index left with ',' i.e test.ind should be

Hi everyone, My goal is to sample from a two-dimensional grid. Consider the following example of code: n.grid <- 500 muA.grid <- seq(-4,4, length=n.grid) muB.grid <- seq(-4,4, length=n.grid) mu.p <- matrix(NA, nrow=n.grid, ncol=n.grid) for(i in 1:n.grid){ for(j in 1:n.grid){ mu.p[i,j] <- dnorm(muA.grid[i], 0, 1)*dnorm(muB.grid[j], 0, 0.5) } } mu.p <-

Hi R-experts, I have a data frame (A) , and a subset (B) of this data frame. I am trying to create a new data frame which gives me all the rows of B, plus the 5th next row(occuring in A). I have used the below code, but it gives me all 5 rows after the matching row. I only want the 5th. FiveDaysLater <- A[c(sapply(match(rownames(B),rownames(A)), seq, length=6))),] Any guidance much

If I use the Ineq library and the Gini function in this way: >Gini(c(100,0,0,0)) I obtain the result 0.75 instead of 1 (that is the perfect inequality). I think Gini's formula in Ineq is based on a formula as reported here: http://mathworld.wolfram.com/GiniCoefficient.html but in the case of perfect inequality: x_1=.......=x_n-1 =0 x_n>0 these formula are equal to 1 - 1/n, not to

Dear List, I try to order the output of a table by the frequencies of the vector I am look at. The object I am looking at is a factor with a lot of levels that were named only once. Therefore it would be much easier to order the output by the frequencies of the levels. E.g. > levels(a) "a" "b" "c" "d" Preferred outcome: table(a) b c a d 10 5 1 1

I have generated some some survival times and censoring indicators. Thus I have an ordered pair for each observation. How do I sample these ordered paris? I only know how to sample from a vector? I would appreciate any help I could get. Thanks Matt

Hi all, I would like to know if it is posible by, someway, to get colMeans from a data.frame with numeric as well as character data, dispersed all over the object. Note that I would like to get colMeans neglecting character data. I am really in need of some function proceeding in that way… All the best Diogo André Alagador [[alternative HTML version deleted]]

Hello, #I have two matrices, eg.: y <- matrix( c(20, NA, NA, 45, 50, 19, 32, 101, 10, 22, NA, NA, 80, 49, 61, 190), ncol=4 ) x <- matrix( c(20, NA, NA, NA, 50, 19, 32, 101, 10, 22, NA, NA, 80, 49, 61, 190), ncol=4 ) #Whereas x contains all NA?s from y plus some additional NA?s. #I want to find the index of these additional NA?s. I think, there must be a very