similar to: Listing the data contents of a package

Hi fellow R-users, I have run into a problem when trying to identify the number of rows in a matrix. Say we have an arbitrary 5 by 5 matrix called temp: temp <- matrix(norm(25), nrow=5) The problem is that nrow(temp[1,]) returns NULL. I would like it to return 1 because in my larger program I am indexing the rows of large matrices according to another variable and I need to test when the

Dear fellow R-users, Is there a function that does the bisection method? I was unable to find one. Thanks in advance. Gregory [[alternative HTML version deleted]]

Im trying to ascertain whether or not the facilities of R are sufficient for solving an optimization problem I've come accross. Because of my limited experience with R, I would greatly appreciate some feedback from more frequent users. The problem can be delineated as such: A utility function, we shall call g is a function of x, n ... g(x,n). g has the properties: n > 0, x lies on the

Dear R users, I'd like to evaluate a vector of characters. For example, say I have a data frame called Data including the field names x1, x2, x3, and I'd like to a list out of paste("Data$x", 1:3, sep=""). How can I get list to evaluate paste("Data$x", 1:3, sep="") as an R object rather than a string? Thanks in advance for you assistance. Gregory

I am looking for an efficient way to solve the following problem. I have a large matrix of continuous values with a small proportion of missing values. Columns correspond to variables where each variable has two measurements, call them A and B. The matrix is such that the columns are in sequence with respect to the variables. I would like to sum up the two measurements for each variable and each

Hi fellow R-users, Are there any text editors that recognize sweave (.rnw) files? I am running Windows Vista and in the past I used Tinn-R for R files but it (surprisingly) doesn't recognize rnw files and does not do any syntax highlighting for them. Thanks in advance, Greg __________________________________________________________________ Make your browsing faster, safer, and

Greetings, I have a seemingly simple task which I have not been able to solve today. I want to construct a symmetric matrix of arbtriray size w/o using loops. The following I thought would do it: p <- 6 Rmat <- diag(p) dat.cor <- rnorm(p*(p-1)/2) Rmat[outer(1:p, 1:p, "<")] <- Rmat[outer(1:p, 1:p, ">")] <- dat.cor However, the problem is that the matrix

Greetings, I have a seemingly simple task which I have not been able to solve today and I checked all of the help archives on this and have been unable to find anything useful. I want to construct a symmetric matrix of arbtriray size w/o using loops. The following I thought would do it: p <- 6 Rmat <- diag(p) dat.cor <- rnorm(p*(p-1)/2) Rmat[outer(1:p, 1:p, "<")] <-

Dear R-users, Say that I have a sequence of zeroes and ones: x <- c(1,1,1,0,0,0,0,1,1,1,0,0,0,0,1,1,1,0,0,0,0) The sequences of ones represent segments and I want to report the starting and endpoints of these segments. For example, in 'x', the first segment starts at location 1 and ends at 3, and the second segment starts at location 8 and ends at location 10. Is there an efficient

Can anyone tell me the trick for obtaining the smoother matrix from smooth.spline when there are non-unique values for x. I have the following code but, of course, it only works when all values of x are unique. ## get the smoother matrix (x having unique values smooth.matrix = function(x, df){ n = length(x); A = matrix(0, n, n); for(i in 1:n){ y = rep(0, n); y[i]=1; yi =

Hi guys im having a problem getting R to numerically integrate for some function, say f(bhat)*optimize(G(bhat)), over bhat. Where id like to integrate this over some finite range, so that here as we integrate over bhat optimize would return a different optimum. For instance consider this simple example for which I cannot get R to return the desired result: f <- function(bhat) exp(bhat) g

Hi everyone, My goal is to sample from a two-dimensional grid. Consider the following example of code: n.grid <- 500 muA.grid <- seq(-4,4, length=n.grid) muB.grid <- seq(-4,4, length=n.grid) mu.p <- matrix(NA, nrow=n.grid, ncol=n.grid) for(i in 1:n.grid){ for(j in 1:n.grid){ mu.p[i,j] <- dnorm(muA.grid[i], 0, 1)*dnorm(muB.grid[j], 0, 0.5) } } mu.p <-

Hello fellow R users, I have a matrix computation that I imagine should be relatively easy to do, however I cannot figure out a nice way to do it. I have two matrices, for example mat1 <- matrix(c(1:5,rep(NA,5), 6:10), nrow=3, byrow=T) mat2 <- matrix(c(2:6, 6:10, rep(NA,5)), nrow=3, byrow=T) I'd like to compute the element-wise average for non-NA entries. Of course (mat1+mat2)/2

I have a dataset with two variables that are factors: 1) Decision Making Satisfaction (DMS), values = A - Completely, B - Mostly, C - Partly, D - Not at all 2) IT Satisfaction values (ITS), values = A - Completely, B - Mostly, C - Partly, D - Not at all I would like to produce a table (matrix) and a chart of the factors, with counts at the cross sections: A B C D A B

Fellow R-users, I have a longitudinal data set with missing values in it. I would like to produce a residual plot for each time using panel.xyplot function but I get an error message. Here's a simple example, library(nlme) set.seed(1544) longdata <- data.frame(ID=gl(10,1,50), y=rnorm(50), time = as.numeric(gl(5,10,50)), x = rnorm(50)) longdata$y[5] <- NA longdata$x[35] <- NA

Hello, Gurus: I tried to test if the sample mean of a dataset is zero. The data has 1500 numbers with a lot of zeros and some small positive numbers. The data range on [0,1] but the distribution is unknown. It is zero inflated anyway. I tried to use the Wilcoxon Signed Ranks test. But I read from this website that it does assume the population pdf is symmetric.

Hello, With the new version 2.2.0, I get strange plots when using the histogram-like option in plot(). For example, a plot of binomial probabilities: > plot(0:10,dbinom(0:10,10,.1), type = "h", lwd = 30) gives me weird fat cirular bars, with mass out at values with low probability. What is the issue here? This never happened with earlier versions. R on Windows XP SP 2 Intel

I would like to be able to place a normal distribution surrounding the predicted values at various places on a plot. Below is some toy code that creates a scatterplot and plots a regression line through the data. library(MASS) mu <- c(0,1) Sigma <- matrix(c(1,.8,.8,1), ncol=2) set.seed(123) x <- mvrnorm(50,mu,Sigma) plot(x) abline(lm(x[,2] ~ x[,1])) Say I want to add a normal

I want to draw a little subplot ("overview") into my detailed plot. It should be placed in say the top right corner and have the size of some legend (like legend(x="topright", inset=0.03, ...) #main plot plot(rnorm(100)) #give little density in corner plot(seq(-2,2,length=300),dnorm(seq(-2,2,length=300)),type="l") I don't want something like par(mfrow=c(1,2)) as

I want to plot something (eg a circle) with a fixed ratio of the x and y axis, or (even better) with a fixed size when I print it. Output should then be a circle (actually it'll be someting more complicated) with radius 5cm and not an ellipse. I'm _sure_ this is not new, but after looking 45min for a solution, I post here... Thanks for help Thomas