search for: nrows

Hi Dear All, This is a function which contains Covariance Ratio and Likelihood Distance values (CVRi, LDi). i want to compute the all row's values, that is run this function for nrow(X) times. The X and Y matrices are;

Dear R-users, I would like to maximize the function g above which depends on 4 parameters (2 vectors, 1 real number, and 1 matrix) using optim() and BFGS method. Here is my code: # fonction to maximize g=function(x) { x1 = x[1:ncol(X)] x2 = x[(ncol(X)+1)] x3 = matrix(x[(ncol(X)+2):(ncol(X)+1+ncol(X)*ncol(Y))],nrow=ncol(X),ncol=ncol(Y)) x4 = x[(ncol(X)+1+ncol(X)*ncol(Y)+1):length(x)]

Hi, You could try: A<- matrix(unlist(read.table(text=" 1 2 3 4 5 6 7 8 9 9 8 7 6 5 4 3 2 1 ",sep="",header=FALSE)),ncol=3,byrow=FALSE,dimnames=NULL) library(matrixStats) ?res1<-t(sapply(split(as.data.frame(A),as.numeric(gl(nrow(A),2,6))),colProds)) ?res1 #? [,1] [,2] [,3] #1??? 4?? 10?? 18 #2?? 63?? 64?? 63 #3?? 18?? 10??? 4

Dear All, I'm dealing with a case, where 'manhattan' distance of each of 100 vectors is calculated from 10000 other vectors. For achieving this, following 4 scenarios are tested: 1) scenario 1: > x<-read.table("query.vec") > v<-read.table("query.vec2") > d<-matrix(nrow=nrow(v),ncol=nrow(x)) > for (i in 1:nrow(v)){ + d[i,]<-

I am new to R and have two scripts written slightly different but should to relatively the same thing but my lack of experience with the program I can not figure out the what I need to do to correct it. The first script gives me a consistent mean fold change values with every run but can generate negative p values for some. For the second version of the script, the fold changes seem to be very

Dear R-developers, I am currently trying to develop a package with some customized container classes and found an issue with the functions NROW and NCOL. I guess that I can simply work around the problem by redefining these functions in my own package (Yet, I do not know whether that will work cleanly everywhere). Nevertheless, I thought that perhaps one might think about to redefine these

...nentiation by squaring. Is there a way to cut down on the number of copies I am making here (I am assuming that the lhs and rhs of matprod() must be different instances). Any feedback appreciated ! Thanks Rory <snip> /* Convenience function */ static void copyMatrixData(SEXP a, SEXP b, int nrows, int ncols, int mode) { for (int i=0; i < ncols; ++i) for (int j=0; j < nrows; ++j) REAL(b)[i * nrows + j] = REAL(a)[i * nrows + j]; } SEXP do_matexp(SEXP call, SEXP op, SEXP args, SEXP rho) { int nrows, ncols; SEXP matrix, tmp, dims, dims2; SEXP x, y, x_, x__;...

...lt;-.data.frame" ) A single object matching '$<-.data.frame' was found It was found in the following places package:base registered S3 method for $<- from namespace base namespace:base with value function (x, i, value) { cl <- oldClass(x) class(x) <- NULL nrows <- .row_names_info(x, 2L) if (!is.null(value)) { N <- NROW(value) if (N > nrows) stop(gettextf("replacement has %d rows, data has %d", N, nrows), domain = NA) if (N < nrows && N > 0L) if (nrows%%...

Hola everyone, Solving this issue would be a huge time saver for analyzing my thesis data, so I'll try to be as concise as possible and hope that someone can give me a hand. I am trying to run a function that I created, which works fine until I try to use it with the by function. That function is listed at the bottom (f3) just in case that might be the issue. Essentially I have compiled a

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  want to print in the console and to have an excel file like this no_GWP                NbOfPolicyClass1[0-1000]     NbOfPolicyClass2[1000-3000]        NbOfPolicyClass3[> 3000] No_GWPMax=8    NbpolicyClass1=5                   NbpolicyClass2=4                            NbpolicyClass3 =3              i have do it like this:!!! data1 <-

Hello R users, I have a set of data frames for which I am tallying row numbers, as shown below. > nrow(mC_Explant) [1] 14480 > nrow(mC_Callus) [1] 23320 > nrow(mC_RegenPlant) [1] 8108 etc. I want to create a new data frame which has the variable names as column headings, and then a single row with the nrow tallies. My first step was this: dfIntron <- c(nrow(mC_Explant),

After some headache with debugging my script, I finally isolated the problem taht I am going to illustrate in the following example. I expected matrix nrow to decrease consistently till 1. Instead, when the matrix is left with one row only, its nrow jumps to 2 because the matrix gets transposed. How come ? Thank you, Maura > B <- c(1,2) > B <- rbind(B,c(3,4)) > B <-

Hello, I gather data from 5 objects and 5 data. frames and would like to join information. join: pb_SM + pb_T + pb_P + pb_F + pb_SJ = total_pb join: sdmdata_SM + sdmdata_T + sdmdata_P + sdmdata_F + sdmdata_SJ =total_sdmdata code: rbind, merge? total_pb<- ?? total_sdmdata<- ?? 1 absvals_SM <- extract(grid_present_SM, absences_10000) presvals_SM <-

Dear all, My questions are that if I have > x<-rnorm(50) > dim(x)<-c(10,5) > y=1:5 > Z<-matrix(0,NROW(x),NROW(y)) > for (j in 1:NROW(y)) Z[,j]<-x[,j]*y[j] 1. Is there any other way to write this without 'for' loop? 2. and if I don't know the dimension of x, which could be only 1 column, how could I write the command without using if (NCOL(x)==1), or

Dear all, I have just sent an email with my problem, but I think no one can see the red part, beacuse it is black. So, i am writing again the codes: rm(list=ls()) #remove almost everything in the memory set.seed(180185) nsim <- 10 mresultx <- matrix(-99, nrow=1000, ncol=nsim) mresultb <- matrix(-99, nrow=1000, ncol=nsim) N <- 200 I <- 5 taus <- c(0.480:0.520) h <-

Hi all, (if me email goes out as html, than my email client don't do as told, and I apologies already.) We need to downscale climate data and therefore first need to expand the climate from 0.5deg to the higher resolution 10min, before we can add high resolution deviations. We basically need to have the original data at each gridcell replicated into 3x3 gridcells. A simple for loop can do

My parallel code is running slower than my non-parallel code! Can someone pls advise what am I doing wrong here? t and tTA are simple matrices of equal dimensions. #NON PARALLEL CODE nCols=ncol(t) nRows=nrow(t) tTA = matrix(nrow=nRows,ncol=nCols) require(TTR) system.time( for (i in 1:nCols) { x = t[,i] xROC = ROC(x) tTA[,i]=xROC } ) user system elapsed 123.24 0.07 123.47 # PARALLEL CODE nCols=ncol(t) nRows=nrow(t) tTA = matrix(nrow=nRows,ncol=nCols) require(doSMP) workers &l...

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

Hello, I am working with a sparse matrix that is approx. 13,900 by 14,100. My goal is to select a row out of the matrix and create a new matrix with that row repeated 13,900 times without having to do any looping. Example: Starting Matrix: exampleMatrix 3 x 4 sparse Matrix of class "dgCMatrix" [1,] 1 . . . [2,] . 1 . 0.5 [3,] . . 1 .. New Matrix:.. newExampleMatrix 3 x 4 sparse