similar to: finding the minimum positive value of some data

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.

Hi all, I cannot think of the technical name of this plot, but I want to create a plot with the data below that looks like two back-to-back horizontal bar plots. Ideally, there would be a vertical line in the center of the plot at zero, and on the right hand side would be 4 bars representing the values for 2007, and on the left side of the vertical line would be the corresponding values for 2005.

useR's, I have several matrices of size 4x4 that I want to calculate means of their respective positions with. For example, consider I have 3 matrices given by the code: mat1 <- matrix(sample(1:20,16,replace=T),4,4) mat2 <- matrix(sample(-5:15,16,replace=T),4,4) mat3 <- matrix(sample(5:25,16,replace=T),4,4) The result I want is one matrix of size 4x4 in which position [1,1] is the

Hi useR's I have created a simple map of the world using the following code: m <- map(xlim=c(-180,180), ylim=c(-90,90)) map.axes() I then create a grid of dimension 36x72 using the code: map.grid(m, nx=72, ny=36, labels=FALSE, col="black") This gives 2592 grid cells. In a separate data set of dimension 36x72, I have 2592 temperature values (some missing values are present)

useR's I am trying to compare two vectors that have the same length. More specifically, I am interested in comparing the corresponding positions of each element in the vector. Consider these two vectors of length 20: v1 <- 2 2 4 NA NA NA 10 NA NA NA NA NA NA NA NA NA NA NA NA NA v2 <- NA 4 NA NA NA NA 10 NA NA NA NA NA NA NA NA NA NA NA

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

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

Hi all, I have a data frame that looks like such: LATITUDE LONGITUDE TEMPERATURE TIME 36.73 -176.43 58.32 1 50.95 90.00 74.39 1 -30.42 5.45 23.26 1 15.81 -109.31 52.44 1 -80.75 -144.95 66.19 2 90.00 100.55 37.50 2

Dear List, I am trying to draw a rectangular plane using the persp function, however I can't seem to get it to work. I want the length along x1 axis to be between 1 and 3 and the length along the x2 axis to be between 1 and 4. All z values for x1 should be equal (say, z=1) because this is a plane, not a cube. Below is my current code. Any help is appreciated Thanks in advance dxc13 x

Hi all, I'm using a certain  procedure to calculate the value of some variable(Bayes risk),B. So I got the values B1, B2, ........, B1000, each under certain input values and using a long procedure. Now, I want to put the values I got in a nummerical vector and find their minimum value. I think c( ) should work.For example if I have only 10 values I could have used

useR's, I want to match the real number elements of a list that has 3 matrices as its elements and then average those numbers. I think I am close, but I can't get it to quite work out. For example, > a <- list(matrix(c(10,NA,NA,12,11, > 10,13,NA,14,12),ncol=2),matrix(c(10,12,15,13,11, > 13,NA,NA,12,10),ncol=2),matrix(c(10,15,NA,13,NA, 13,12,NA,NA,10),ncol=2)) > a [[1]]

useR's, I want to apply this function to the columns of a data frame: u[u >= range(v)[1] & u <= range(v)[2]] where u is the n column data frame under consideration and v is a data frame of values with the same number of columns as u. For example, v1 <- c(1,2,3) v2 <- c(3,4,5) v3 <- c(2,3,4) v <- as.data.frame(cbind(v1,v2,v3)) uk1 <- seq(min(v1) - .5, max(v1) + .5,

Hi, I have a matrix BEE and want to find the row and column numbers of the minimum value in that matrix. The command which(BEE==min(BEE)) returns only one value which, I take, is the position of the minimum in a vector with as many elements as the matrix. Is there a quick and simple way of getting row and column numbers? Thanks, Gonçalo [[alternative HTML version deleted]]

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, I am writing a program in which the input can be multidimensional. As of now, to hold the input, I have created an n by m matrix where n is the number of observations and m is the number of variables. The data that I could potentially use can contain well over 20,000 observations. Can a simple matrix be used for this or would it be better and more efficient to create an external

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

RUsers, I am trying (with little success) to determine how to combine unique and min to do some data frame manipulations and I could use a little advice. I have tried various combinations of 'unique', 'min' and 'apply' with no luck. Given this simple example data (x, y) x<-c(10, 10, 12, 13, 15, 16 ,17, 17, 17) y<-c(112, 117, 111, 117, 114, 113, 119, 121, 130)

Hi all, I have posted similar questions regarding this topic, but I just can't seem to get over the hump and find a straightforward way to do this. I have attached my file as a reference. Basically, the attached file is a 5 degree by 5 degree grid of the the world (2592 cells), most of them are NA's. I just want to be able to plot this grid over a world map and color code the cells. For

Friends If I have a matrix such as... [,1] [,2] [1,] 7 7 [2,] 7 9 [3,] 9 2 [4,] 7 9 And I want to find the row number that has the minimum value of column 2 (row 3 in this case) how can I do it? Is there a simple way? cheers Worik [[alternative HTML version deleted]]