similar to: Regress a matrix on another matrix column by column

Hi, everyone. I need to run lm with the same response vector but with varying predictor vectors. (i.e. 1 response vector on each individual 6,000 predictor vectors) After looking through the R archive, I found roughly 3 methods that has been suggested. Unfortunately, I need to run this task multiple times(~ 5,000 times) and would like to find a faster way than the existing methods. All three

I need to force a coxph() function in R to use a pre-calculated set of beta coefficients of a gene signature consisting of xx genes and the gene expression is also provided of those xx genes. If I try to use "coxph()" function in R using just the gene expression data alone, the beta coefficients and coxph$linear.predictors will change and I need to use the pre-calcuated linear predictor

Hi all, I am trying to multiply each column of a matrix such to have a unique resulting vector with length equal to the number of rows of the original matrix. In short I would like to do what prod(.) function in Matlab does, i.e. A <-matrix(c(1:10),5,2) V = A[,1]*A[,2] Thank you Graziano [[alternative HTML version deleted]]

hello all, I have a data frame and I want to create a column which assigns a letter based upon the value in another column. The data column has velocities ranging from 0 to 1000. So for example, for velocities between 0 and 300 I'd like to assign the letter "A" in the new column, for 300-600, "B" and so on and so forth. How would I do this? Thank you very much! Mehdi

Hi all, I have a multiple-linear regression problem. There are 13 columns of data, the whole data matrix is: n x 13, where n is the number of samples. Now I want to regress EACH of the first 12 columns onto the 13th column, with 2-parameter linear model y_i = b0 + b1 * x_i, where i goes from 1 to n, and b0 is the intercept. How do I create a design matrix to do the 12-column regression

Dear R helpers Suppose x  <- c(1:3) y  <- matrix(1:12, ncol = 3, nrow = 4) > y      [,1] [,2] [,3] [1,]    1    5    9 [2,]    2    6   10 [3,]    3    7   11 [4,]    4    8   12 I wish to multiply 1st column of y by first element of x i.e. 1, 2nd column of y by 2nd element of x i.e. 2 an so on. Thus the resultant matrix should be like > z      [,1]   [,2]    [,3] [1,]    1   

Hi, I am looking for two ways to speed up my computations: 1. Is there a function that efficiently computes the 'sandwich product' of three matrices, say, ZPZ' 2. Is there a function that efficiently computes the determinant of a positive definite symmetric matrix? Thanks, S.A. [[alternative HTML version deleted]]

Hi Everybody, I have a matrix of about 45 columns. Some of the rows contain zeros. Using >data1<-data[complete.cases(data),], I can remove the "NA" rows. But I am unable to tackle that of zeros. Can anybody give me an idea of how to remove rows containing zeros in a matrix. Thanks so much Best Ogbos [[alternative HTML version deleted]]

Dear All   I would like to convert matrix rows to columns. I am thinking the t() function should help, but am having a hard time converting the matrix into the dimensions I would like them to. Example:   a <-matrix(c(1:30),ncol=3) gives me:[,1] [,2] [,3] [1,] 1 11 21 [2,] 2 12 22 [3,] 3 13 23 [4,] 4 14 24 [5,] 5 15 25 [6,] 6 16 26 [7,] 7 17

useR's, I have a matrix given by the code: mat <- matrix(c(rep(NA,10),1,2,3,4,5,6,7,8,9,10,10,9,8,NA,6,5,4,NA,2,1,rep(NA,10),1,2,3,4,NA,6,7,8,9,10),10,5) This is a 10x5 matrix containing missing values. All columns except the second contain missing values. I want to delete all columns that contain ALL missing values, and in this case, it would be the first and fourth columns. Any column

Hi, I have a matrix that looks like this a <- c(1,1,1,1,2,2,3,3,3,3) b <- c(2,2,2,3,4,4,4,5,5,6) c <- c(1,2,3,4,5,6,7,8,9,10) M <- matrix(nr=10,nc=3) M[,1] <- a M[,2] <- b M[,3] <- c > M [,1] [,2] [,3] [1,] 1 2 1 [2,] 1 2 2 [3,] 1 2 3 [4,] 1 3 4 [5,] 2 4 5 [6,] 2 4 6 [7,] 3 4 7

Hi, This might seem like a simple question but at the moment I am stuck for ideas. The columns of my matrix in which some data is stored are of this form: X1 Y1 X2 Y2 X3 Y3 ... Xn Yn with n~100. I would like to look at just the X values (i.e. odd column numbers). Is there an easy way to loop round extracting only these columns? Any help would be appreciated.

Hi, I have this lame question. I want to convert a list (each with varies in length) to matrix with same row length by eliminating vectors outside the needed range. For example: l<-list(NULL) l[[1]]=1,2,3.7 l[[2]]=3,4,5,6,3 l[[3]]=4,2,5,7 l[[4]]=2,4,6,3,2 l[[5]]=3,5,7,2 #so say I want to only have 4 rows and 5 column in my matrix (or data.frame) and eliminating the 5th index value in l[[2]]

Hi, I have a correlation matrix of about 3000 items, i.e., a 3000*3000 matrix. For each of the 3000 items, I want to get the top 50 items that have the highest correlation with it (excluding itself) and generate a data frame with 3 columns like ("ID", "ID2", "cor"), where ID is those 3000 items each repeat 50 times, and ID2 is the top 50 correlated items with ID,

I have a data frame "reading" that includes a logical variable "OLT" along with response variable "Reading" and predictor "True" (BOTH are numeric variables; it's "True" as in the true value). When I suppress the intercept, model.matrix gives me OLTTRUE and OLTFALSE columns. Why? Can I do anything to prevent it? > r <-

Hi- Unfortunately, I just found out about the patch that was available for tru64 privsep. I was entirely unaware that there was a lack of support. Will the patch be considered for approval if it is applied to 3.4p1, or does it have to be done against -current? The reason I'm asking is that I have 3.4p1 working as is, so I know if I have a problem it is likely related to the patch and not

Within a very large matrix composed of a mix of values and NAs, e.g, matrix A: [,1] [,2] [,3] [1,] 1 NA NA [2,] 3 NA NA [3,] 3 10 17 [4,] 4 12 18 [5,] 6 16 19 [6,] 6 22 20 [7,] 5 11 NA I need to be able to consecutively number, in new columns, the non-NA values within each column (i.e. A[1,1] A[3,2] and A[3,3] would all be set to one, and

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 I have a rectangular matrix of size 920 by 85. I'd like to coerce it into a square matrix such that all row/col names are present in the new matrix and the additional values are zero. As an example: A B C D A 1 2 3 4 E 5 6 7 8 F 9 10 11 12 Would be coerced to: A B C D E F A 1 2 3 4 5 9 B 2 0 0 0 6 10 C 3 0 0

I have following matrix : a = matrix(rnorm(36), 6) Now I want to replace the lower-triangular elements with it's upper-triangular elements. That is I want to make a symmetric matrix from a. I have tried with lower.tri() and upper.tri() function, but got desired result. Can anyone please tell me how to do that?

Hello everyone,   I have a matrix like :   mat <- matrix(rnorm(12*3), 3)   Now I want to break that matrix in 4 parts each of them are matrix of (3x3) and put those 4 matrices in a "list" object of length 4   Can anyone please tell me how to do that? Get your new Email address! Grab the Email name you&#39;ve always wanted before someone else does! [[alternative HTML