similar to: creating a database

useR's, I have used expand.grid() several times and like the results it gives me. I am now trying something with it that I have not been able to get to work. For any n column matrix I would like to run this function on those n columns and store the results. For example, if my matrix has 1 column then this is just expand.grid(x = column1). If my matrix has two columns, then I want

useR's, First, I would like to say thanks to John Fox for providing this segment of code to perform intersection for multiple sets: intersection <- function(x, y, ...){ if (missing(...)) intersect(x, y) else intersect(x, intersection(y, ...)) } I want to execute this function on the rows of a matrix I have: Ik.mat.test <- matrix(c(2,3,6,1,2,6,6,1,2),byrow=T,nrow=3) > Ik.mat.test

useR's, Consider: y <- c(20, 25, 30) > m <- matrix(c(0.0,1,NA,0.5,1.25,0.75, 0.5, NA, > NA),byrow=TRUE,nrow=3,ncol=3) > m [,1] [,2] [,3] [1,] 0.0 1.00 NA [2,] 0.5 1.25 0.75 [3,] 0.5 NA NA For each numeric value, I want to replace them with their corresponding y-value. The result should look like (here, each row represents a variable rather than the columns):

useR's, Is there a way to create a temporary array (or matrix) in R to hold values, then drop or delete that temporary array from memory once I do not need it anymore? I am working with multidimensional arrays/matrices and I frequently perform multiple operations on the same matrix and rename it to be another object. I want to be able to delete the older versions of the array/matrix to free

useR's. I am working with an algorithm in which I will need to create combinations of all the points I have in a matrix. When I have 2 variables, I simply use expand.grid() to do this. Sometimes I am faced with 3 or more variables and if I run expand.grid(), R cannot process it due to the huge size. Is there any efficient way to workaround this? Thanks, Derek -- View this message in

Hi I am practically new to R, and need to construct connection diagrams, I have a table of data, of nodes in vertical rows, and horizontally the number of outgoing connections to other nodes, and the indices of these nodes, each in a column, so some columns are used, and some are not, based on how many connections I have the node is identified by these variables (dimension, wave number,

Consider a data frame (x) with 2 variables, x1 and x2, having equal values. It looks like: x1 x2 1 1 2 2 3 3 Now, consider a second data frame (xk): xk1 xk2 0.5 0.5 1.0 0.5 1.5 0.5 2.0 0.5 0.5 1 1.0 1 1.5 1 2.0 1 0.5 1.5 1.0 1.5 1.5 1.5 2.0 1.5 0.5 2 1.0 2 1.5 2 2.0 2 I have written code to calculate some differences between these

useR's, I am trying to find a quick way to change some values in a list that are subject to a condition to be NA. Consider the 3x1 matrix: delta <- matrix(c(2.5,2.5,1), nrow = 1) And consider the list named v that has 3 elements > v v[[1]] [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] [1,] 4.25 3.25 2.25 1.25 0.25 0.75 1.75 2.75 3.75 4.25

Hi, I am inquiring as to what are the best practices with respect to storing and manipulating ordered multi-dimensional arrays. For example, suppose I have a sequence of time-varying covariance matrices of asset returns. The data is ordered, but the ordering is not necessarily regular (e.g. daily data omitting weekends and holidays, etc.). The data array is say, N x N x T. For example, the

useR's I have a matrix from which I want to take multiple subsets from, according to a particular scheme I will now describe. The matrix below (mat) is 5x5, and I want to take 9 subsets of it, each of dimension 3x3. The best way to explain what the result should look like is with the following: > dat <- c(3,6,1,9,12,9,2,10,6,5,3,13,1,4,8,9,4,6,10,11,2,7,3,5,10) > miss <-

useR's, This is a follow up question to one I previously asked. Consider the 3-element list below > res [[1]] [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] [1,] NA NA NA 1.25 0.25 0.75 NA NA NA NA NA NA 1.25 0.25 [2,] 1.25 0.25 0.75 NA NA NA NA NA NA 1.25 0.25 0.75 NA NA [3,] NA NA NA NA NA

Dear list, I am trying to construct a perspective plot of a 2D triangle, or pyramid. I can easily do the one dimensional plot (code below), but I can't figure out how to do it in a perspective plot for two input variables. Does anyone have a simple solution? Thanks! Derek #code for a triangle u <- seq(-1,1,.001) tri <- (1-abs(u)) plot(tri~u,type="l",main="Second

useR's, I would like to know if there is a way to avoid using FOR loops to perform the below calculation. Consider the following data: > x [,1] [,2] [,3] [1,] 4 11 1 [2,] 1 9 2 [3,] 7 3 3 [4,] 3 6 4 [5,] 6 8 5 > xk Var1 Var2 Var3 1 -0.25 1.75 0.5 2 0.75 1.75 0.5 3 1.75 1.75 0.5 4 2.75 1.75 0.5 5 3.75 1.75

useRs, I am looking to find the minimum positive value of some data I have. Currently, I am able to find the minimum of data after I apply some other functions to it: > x [1] 1 0 1 2 3 3 4 5 5 5 6 7 8 8 9 9 10 10 > sort(x) [1] 0 1 1 2 3 3 4 5 5 5 6 7 8 8 9 9 10 10 > diff(sort(x)) [1] 1 0 1 1 0 1 1 0 0 1 1 1 0 1 0 1 0 > min(diff(sort(x))) [1] 0

useR's, Does anyone know of an efficient way to change the values in a list to different numbers stored in an object? For example, consider the following: y <- matrix(c(20, 13, 25, 10, 17), ncol = 1) > res [[1]] [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] [1,] NA NA NA 1.25 0.25 0.75 NA NA NA NA NA NA 1.25 0.25 [2,]

useR's, I am trying trying to find out if there is a faster way to do a certain computation. I have successfully used FOR loops and the apply function to do this, but it can take some time to fully compute, but I was wondering if anyone may know of a different function or way to do this: > x [1] 1 2 3 4 5 > xk [1] 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 I want to do:

useR's, I want to randomly generate 500 numbers from the standard normal distribution, i.e. N(0,1), but I only want them to be generated in the range -1.5 to 1.5. Does anyone have a simple way to do this? Thanks, dxc13 -- View this message in context: http://www.nabble.com/simple-random-number-generation-tp18642611p18642611.html Sent from the R help mailing list archive at Nabble.com.

useR's I am trying to color the points on a scatter plot (code below) with two colors. Red for values 0.5 -1.0 and blue for 0.0 - .49. Does anyone know a easy way to do this? x <- runif(100, 0, 1) y <- runif(100, 0, 1) plot(y ~ x, pch=16) Thanks, dxc13 -- View this message in context: http://www.nabble.com/color-ranges-on-a-2D-plot-tp14893457p14893457.html Sent from the R help

All, I have been terribly pleased with openbsd 3.2 I was using it as a mail/samba server with postifx on a pentium pro 200 with 1 gig of memory. Well I wanted to add a larger harddrive than what I have in it now only 6.4 gig. Well the machine would not see it and for some reason after hours and hours of trying I can't get a tekram 395UW and a 18gig scsi to be the boot drive and having failed

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