similar to: rowSums()

Say I have a tab-delimited table I want to read into R. What should I expect to happen if some of the entries contain the character " ' "? I thought it would read the file fine, but that is not what happens. Instead, all the values in between two " ' "s get read into one field, and things are just seriously messed up. Is this a bug, and besides removing the offending

I have a function that I am currently using very inefficiently. The following are needed to illustrate the problem: set.seed(12345) dat <- matrix(sample(c(0,1), 110, replace = TRUE), nrow = 11, ncol=10) mis <- sample(1:110, 5) dat[mis] <- NA theta <- rnorm(11) b_vector <- runif(10, -4,4) empty <- which(is.na(t(dat))) So, I have a matrix (dat) with some values within the matrix

I have a data set where I want the correlations between 2 variables conditional on a students grade level. This code works just fine. by(tmp[,c('mtsc07', 'DCBASmathscoreSPRING')], tmp$Grade, cor, use='complete', method='pearson') However, this generates an error by(tmp[,c('mtsc07', 'DCBASmathscoreSPRING')], tmp$Grade, cor, use='complete',

Hello, I came across a problem when building a randomForest model. Maybe someone can help me. I have a training- and a testdataset with a discrete response and ten predictors (numeric and factor variables). The two datasets are similar in terms of number of predictor, name of variables and datatype of variables (factor, numeric) except that only one predictor has got 20 levels in the training

Hello. I am trying to load the rJava package in R-2.7.2 (Windows XP 64-bit RGui) and get the following error message even though the mentioned .dll file is located at the directory listed in the error message. I have tried to uninstall and reinstall the package but that does not resolve the problem. Then uninstallation and re-installation of R did not resolve the issue either. Any suggestions are

I wonder if there is a more efficient way to do this task. Suppose I have two data frames, such as d1 <- data.frame(x = c(1,2,3), y = c(4,5,6), z = c(7,8,9)) d2 <- d1[, c('y', 'x')] The first dataframe d1 has more variables than d2 and the variable columns are in a different order. So, what I want to do is compare the two frames on the variables that are common between

Friends I'm not seeing why the following occurs: > T1 <- (A1 - A2) %*% D > T2 <- (A1 %*% D) - (A2 %*% D) > identical(T1, T2) [1] FALSE Harold > dput(A1) new("dsCMatrix" , i = c(0L, 1L, 2L, 3L, 0L, 1L, 4L, 2L, 3L, 5L) , p = c(0L, 1L, 2L, 3L, 4L, 7L, 10L) , Dim = c(6L, 6L) , Dimnames = list(NULL, NULL) , x = c(5, 5, 5, 5, 5, 5, 10, 5, 5, 10)

The integral of any probability density from -Inf to Inf should equal 1, correct? I don't understand last result below. > integrate(function(x) dnorm(x, 0,1), -Inf, Inf) 1 with absolute error < 9.4e-05 > integrate(function(x) dnorm(x, 100,10), -Inf, Inf) 1 with absolute error < 0.00012 > integrate(function(x) dnorm(x, 500,50), -Inf, Inf) 8.410947e-11 with absolute error <

Suppose I have the following matrix > class(cov_50) [1] "matrix" > cov_50 [,1] [,2] [1,] 0.3201992 2.308084 [2,] 6.7312928 5.719641 I then use the following function via apply and get the desired output, a list signif <- function(x) which(abs(x) > 1.96) apply(cov_50, 1, signif) > apply(cov_50, 1, signif) [[1]] [1] 2 [[2]] [1] 1 2 However, I can't

I'm finalizing development of a package that will include a vignette. Without the vignette, the package builds fine with no warnings and is ready for distribution. Now, I am following the directions for developing vignettes "Sweave, Part II: Package Vignettes" by Friedrich Leisch. I am using a windows XP machine (other session info below). Here is what I have done. 1) I add the

While building a package, I see the following: * checking R code for possible problems ... NOTE cheat.fit: no visible binding for global variable 'Zobs' plot.jml: no visible binding for global variable 'Var1' I see the issue has come up before, but I'm having a hard time discerning how solutions applied elsewhere would apply here. The entire code for both functions is below,

I've built a package that contains only two functions for a test run. They are: g <- function(x){ x <- x^2 class(x) <- "foo" x } print.foo <- function(x, ...){ cat("This is a test:\n") cat(x, "\n") invisible(x) } Simply testing these functions in the R workspace prior to a build yields: > g(1:5) This is a test: 1 4 9 16 25 Now, I

I know this comes up, but I didn't see my exact issue in the archives. I have variables in a dataframe that need to be recoded. Here is what I'm dealing with I have a factor called aa > class(aa) [1] "factor" > table(aa) aa * 0 1 2 3 A B C D L N T 0 0 1908 725 2089 0 0 67 0 0 2 1 6 I need to recode

R-helpers, Below is a simple example of some output that I am getting while trying to work with a data frame in R 2.12.1 for Mac. ----- > testdat <- data.frame(matrix(ncol=10, nrow=10)) > colnames(testdat) <- c('a','b','c','d','e','f','g','h','i','j') > testdat[seq(1,10,3),] <-

I'm not certain I am using the lattice plot correctly here. Below is reproducible code. Suppose I have two data frames, such as: set.seed(1234) datA <- data.frame(condition = gl(3, 100), scores = c(rnorm(100), rnorm(100, 1,1), rnorm(100, 2,1))) datB <- data.frame(condition = gl(3, 1000), scores = c(rnorm(1000, 3,1), rnorm(1000, 4,1), rnorm(1000, 5,1))) I would like to plot the

Suppose I have data such as the following set.seed(12345) tmp <- data.frame(var1 = rnorm(100), var2 = rnorm(100), var3=rnorm(100, 10, 30)) tmp1 <- data.frame(vars = with(tmp, c(var1, var2, var3)), type = gl(3, 100)) var3 is on a different scale, but I create the following plot, which looks terrible as a result bwplot(~ vars|type, tmp1, layout = c(1,3), ) Of course, I can

Suppose I have the following function myFun <- function(formula, data){ f <- formula(formula) dat <- model.frame(f, data) dat } Applying it with this sample data yields a new dataframe: qqq <- data.frame(grade = c(3, NA, 3,4,5,5,4,3), score = rnorm(8), idVar = c(1:8)) dat <- myFun(score ~ grade, qqq) However, what I would like is for the resulting dataframe (dat) to include

I have not used POSIX classes previously and now have a need to use them. I have sports data with times of some athletes after different events. I need to perform some simple analyses using the times. I think I've figured out how to do this. I just want to confirm with others who have more experience that this is indeed the correct approach. If not, please suggest a more appropriate way.

I have constructed the following functions and need a little clarification: ### function to fit the model parameters jml.fit <- function(dat, con = 1e-3, bias=FALSE, ...){ do stuff ... } ### default function which calls jml.fit jml.default <- function(dat, con = 1e-3, bias=FALSE, ...){ result <- jml.fit(dat, con = 1e-3, bias) result$call <- match.call() class(result) <-

I need to wrap a loop inside a function and am having a small bit of difficulty getting the results I need. Below is a replicable example. # define functions pcm <- function(theta,d,score){ exp(rowSums(outer(theta,d[1:score],'-')))/ apply(exp(apply(outer(theta,d, '-'), 1, cumsum)), 2, sum) } foo <- function(theta,items, score){ like.mat <-