search for: ncols

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)]

Hello I am using the step function in order to do backward selection for a linear model of 52 variables with the following commands: object<-lm(vars[,1] ~ (vars[,2:(ncol(predictors)+1)]-1)) BackS<-step(object,direction="backward") but it isn't dropping any if the variables in the model, but there are lots of not significant variables as you can see here >

Dear ALL I have this function in R: func_LN <- function(data){ med_ge <- matrix(c(rep(NA,nrow(data)*ncol(data))), nrow = nrow(data), ncol=ncol(data), byrow=TRUE) T <- matrix(c(rep(NA,length(n)*ncol(data))), nrow = length(n), ncol=ncol(data), byrow=TRUE) Tdiff<- matrix(c(rep(NA,length(n)*ncol(data))), nrow = length(n), ncol=ncol(data), byrow=TRUE) T1<- c(rep(NA,ncol(data)))

...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__; int i,j,e...

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(doS...

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 expeRts, I have two matrices A and B. They have the same number of columns but possibly different number of rows. I would like to compare each row of A with each row of B and check whether all entries in a row of A are less than or equal to all entries in a row of B. Here is a minimal working example: A <- rbind(matrix(1:4, ncol=2, byrow=TRUE), c(6, 2)) # (3, 2) matrix B <-

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 <-

Dear R users, I have problem with extracting coefficients from a object. Here, X (predictor)and Y (response) are two matrix , I am regressing X ( dimensions 10 x 20) on each of columns of Y[,1] (10 x 1) and want to store the coefficient values. I have performed a Elastic Net regression and I want to store the coeffcients in each iteration. I got an error message . I do not

Dear addresses, I need perform a batch of 10 000 simulations for each of 4 options considered. (The idea is to obtain the parameter estimates in a heteroskedastic linear regression model - with additive or mixed heteroskedasticity - via the Kenward-Roger small-sample adjusted covariance matrix of disturbances). For this purpose I wrote an R program which would capture all possible options (true

The help has > Description: > 'nrow' and 'ncol' return the number of rows or columns present in 'x'. > 'NCOL' and 'NROW' do the same treating a vector as 1-column matrix. and > x: a vector, array or data frame I'm proposing to extend these two convenience functions to also work ``correctly'' for generalized versions of

Dear all, I am trying to run a loop in my codes, but the software returns an error: "subscript out of bounds" I dont understand exactly why this is happenning. My codes are the following: 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

Hi everyone and Achim, Achim, I appreciate your help about the function "NCOL". When I use "NCOL" instead of "ncol", I can find out the number of columns (number of time series) in the presence of only one time series (one variable, one column). Now I want to know how I can find out the column names of the zoo objects? In case of more than one time series, the

Hi, I'm quite new to R (1 month full time use so far). I have to run loop regressions VERY often in my work, so I would appreciate some new methodology that I'm not considering. #--------------------------------------------------------------------------------------------- y<-matrix(rnorm(100),ncol=10,nrow=10) x<-matrix(rnorm(50),ncol=5,nrow=10) #Suppose I want to run the

http://biomet.oxfordjournals.org/cgi/reprint/86/3/677 biometrika1999 http://biomet.oxfordjournals.org/cgi/reprint/94/4/1006 biometrika2000 Hi All: I just want to try some luck. I am currenly working on my project,one part of my project is to reanalysis the kenward cattle data by using the method in Mohsen's paper,but I found I really can get the same or close output as he did,so,any

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 goal is to store the DWT coefficients from a number of time series in such a way to be able to extract subsets satisfying giben conditions. I have defined the following 11 matrices whose x-axis represent time intervals and y-axis represent the number of time series: MS <- 11 d1.mat <- matrix (data=list(), nrow=TotNumCycles, ncol=2^(MS-1)) d2.mat <- matrix (data=list(),

Dear all, I am a new user in r and I am facing some problems with the quantile regression specification. I have two matrix (mresultb and mresultx) with nrow=1000 and ncol=nsim, where I specify (let's say) nsim=10. Hence, the columns in my matrix represents each simulation of a determined variable. I need to regress each column of mresultb on mresultx. My codes are the following:

I don't know whether this belongs to r-devel or rather r-help. Under RW1.11 --nsize=8M --vsize=512M I could n <- 500000 m <- 20 x <- matrix(rnorm(n*m), ncol=m, nrow=n) gc() > n <- 500000 > m <- 20 > x <- matrix(rnorm(n*m), ncol=m, nrow=n) > gc() free total (Mb) Ncells 8190509 8388608 160 Vcells 57033698 67108864 512 # under RW1.20 --vanilla

Dear useRs, i have certain commands for some operations in R. They are good if you have a small dataset but my dataset, apart from what i used in the recent past, is prety large. I want to convert these massive sets of commands into a simple loop. Your help is required on it thanks in advance eliza kindly note: "e" is matrix whose each column has to be executed into a distance vector