similar to: Got "Unexpected ELSE error"

Hi! I've noticed the ecdf() R code (R ver. 2.5.0) contains two call to sort: --- [R-code] --- ecdf <- function(x) x <- sort(x) n <- length(x) if (n < 1) stop("'x' must have 1 or more non-missing values") vals <- sort(unique(x)) rval <- approxfun(vals, cumsum(tabulate(match(x, vals)))/n, method

I am looking for a function like my.blockwisesum(vector, n) that computes sums of disjoint subsequences of length n from vector and can work with vector lengths that are not a multiple of n. It should give me for instance my.blockwisesum(1:10, 3) == c(6, 15, 24, 10) Is there a builtin function that can do this? One could do it by coercing the vector into a matrix of width n, and then use

I want to make a plot, but instead of showing _numerical_ values, I would like to show _symbolic_ values. For example, I want to plot a function y = a x + b, where x varies between Xmin and Xmax. I would like the plot to show, in the x-axis, the strings Xmin and Xmax, instead of their numeric values. Is it possible? Alberto Monteiro

Dear All, I wonder if there is any R function to generate a sequence of vectors from existing ones. For example: x 1<- c(1,2,3) x2 <- c(4,5) x3 <- c(6,7,8) The desired output is a list of all 3*2*3 = 18 possible combinations of elements of x1,x2 and x3. One element for example is (1,4,6). Many thanks in advance, Bernard

Hi R-users, I am trying to divide a vector (say X) into equal frequency bins. If one uses the hist() function, then a histogram is plotted, but with bins of equal widths, and not with bins having the same number of data points. I have then tried the histogram() function as follows: histogram(X, nint=10, breaks=NULL, equal.widths=F) This works as I want. However, I can't extract which

Hello there! My operating system is Windows XP, my version of R is the latest (R-2.5.0). Recently I have downloaded the package "mvtnorm" and a problem with the command "pmvnorm" occured. Trying to enter the lines ... A <- diag(3) A[1,2] <-0.5 A[1,3] <- 0.25 A[2,3] <- 0.5 pvmnorm(lower=c(-Inf,-Inf,-Inf), upper=c(2,2,2),mean = c(0,0,0), corr=A) I got the following

En innebygd og tegnsett-uspesifisert tekst ble skilt ut... Navn: ikke tilgjengelig Nettadresse: https://stat.ethz.ch/pipermail/r-help/attachments/20080212/d6012c8f/attachment.pl

Hi R, I have a matrix A, A= [,1] [,2] [1,] a u [2,] b v [3,] c x [4,] d x [5,] e x I want to put the 2nd column of this matrix in a vector without duplicates. i.e., my vector v should be (u, v, x), whose length is 3. Can anybody help me on this? Thanks in advance Shubha. [[alternative HTML version deleted]]

Hi I have a little function that takes a vector v and an integer i. I want to manipulate v[-i] (to give v.new, say) and then put (unmanipulated) v[i] back into the appropriate place. For example, f <- function(v,i){ v.new <- v[-i]+10 return(c(v.new[1:(i-1)],v[i],v.new[i:length(v.new)])) } (my example is adding 10 to v[-i], but the real version is the solution of a complicated

Dear R-Helpers, I want to compare the results of outputs from glmmPQL and lmer analyses. I could do this if I could extract the coefficients and standard errors from the summaries of the lmer models. This is easy to do for the glmmPQL summaries, using > glmm.fit <- try(glmmPQL(score ~ x*type, random = ~ 1 | subject, data = df, family = binomial), TRUE) > summary(glmmPQL.fit)$tTable

Dear R users, how can I extrapolate values listed in the summary of an lm model but not directly available between object values such as the the standard errors of the calculated parameters? for example I got a model: mod <- lm(Crd ~ 1 + Week, data=data) and its summary: > summary(mod) Call: lm(formula = Crd ~ 1 + Week, data = data, model = TRUE, y = TRUE) Residuals: Min

I have the following csv file: name,x,y,z category,delta,gamma,epsilon a,1,2,3 b,4,5,6 c,7,8,9 I'd like to create a numeric matrix of just the numbers in this csv dataset. I've tried the following program: sample.data <- read.csv("sample.csv") numerical.data <- as.matrix(sample.data[-1,-1]) However, print(numerical.data) returns what appears to be a matrix of

Hi If string <- "xyz" f <- function(x){1 + sin(cos(x)) + exp(x^2)} How do I manipulate "string" and f() to give the string "1 + sin(cos(xyz)) + exp(xyz^2)" ? -- Robin Hankin Uncertainty Analyst National Oceanography Centre, Southampton European Way, Southampton SO14 3ZH, UK tel 023-8059-7743

Hello, I have x and y data to plot (synthetic example): x <- seq(0,4*pi,by=0.1) y <- sin(x) I then want to plot (x,y) in those points where abs(y) is smaller than 0.5. As a first approximation plot(x[abs(y) < 0.5],y[abs(y) < 0.5]) is quite close - however I want to plot with lines, i.e. type="l", and then I get solid lines connecting the endpoint of one

I am trying to do the simplest thing in the world. The following works: aaa <- ifelse(aaa==5, 6, 7) But if I want to change the if...else syntax instead, it gives errors and assigns 7 to aaa. Here is the problem code: aaa <- 5 if ( aaa==5 ) { aaa <- 6 } else { aaa <- 7 } Here is the output: > aaa <- 5 > if ( aaa==5

Hello, I am facing a problem with lapply which I ''''think''' may be a bug. This is the most basic function in which I can reproduce it: myfun <- function() { foo = data.frame(1:10,10:1) foos = list(foo) fooCollumn=2 cFoo = lapply(foos,subset,select=fooCollumn) return(cFoo) } I am building a list of dataframes, in each of which I want to keep only column

Dear R gurus, I have a function "goftests" that receives the following arguments: * a vector "x" of data values; * a distribution name "dist"; * the dots list ("...") containing a list a parameters to pass to CDF function; and calls several goodness-of-fit tests on the given data values against the given distribution. That is: ##### BEGIN CODE SNIP #####

Hi This is a difference between the way matrices and data frames work I guess. I want to replace the NA values in a data frame by 0, and the code works as long as the data frame in question actually includes an NA value. If it doesn't, there is an error: df <- data.frame(c1=c(1,1,1),c2=c(2,2,NA)) df[is.na(df)] <- 0 df df <- data.frame(c1=c(1,1,1),c2=c(2,2,2)) df[is.na(df)] <-

Thanks Dimitris!!! That's much clearer now. Still have a lot of work to do this weekend to understand every bit but your code will prove very useful. Cheers, Aziz -----Original Message----- From: Dimitrios Rizopoulos [mailto:Dimitris.Rizopoulos at med.kuleuven.be] Sent: May 12, 2006 4:35 PM To: Chaouch, Aziz Subject: RE: [R] Maximum likelihood estimate of bivariate

Hi, I know S manuals used to warn against using the same names for a variable and a function, but I have never seen that cause problems in R, so I usually don't pay much attention to it. Which is why the following behaviour came as a surprise: > bar <- function() 1 > foo <- function(bar = bar()) { + bar + } > foo(9) [1] 9 > foo() Error in foo() : recursive default