similar to: possible arrangements of across sample ties for runs test

Hi, I need to scan some files, and then do a boxplot graph of them. I also save the output from the boxplot function, so I can process the data later. For example, I need to scan 2 (it can be x, 0<x) files here. A<-scan(F1)/100; B<-scan(F2)/100; Now let's try graph it. N1 is the label for F1, and so on. bitmap(file=Name, type="png16m")

Hallo! I found a question exactly as mine, but I did not found an answer. Therefore?I post this again - hopefully there will be an answer! Thanks in advance! karl From: Berta <ibanez> Date: Tue, 27 Feb 2007 18:58:48 +0100 Hi R-users, I want to calculate the sample size needed to carry out a 2-sample proprotion test. I have the hypotesized treatment probability of success (0.80), the

Hello. I am probably wrong... I am wondering if it could have a mistake in the code of the ansari.test function. For me, it seems that the function do not recover the p value at the correct side of the normal law N(0, 1) when it use the normal approximation (presence of ties) in a one tailed test. Exemple : quanti<-c(197, 205, 228, 234, 237, 195, 233, 226, 244, 227, 259, 185, 198, 253, 207,

I'm trying to figure out R, a piece at a time, hours at a time... I was trying to copy the sample function in, "An Introduction to R" (for version 2.1.0) by W. N. Venables, D. M. Smith, page 42. Section 10.1 "Simple examples" provides a sample function which I tried to duplicate (I'm using Mac OS X 10.3.9, and "R for Mac OS X Aqua GUI v1.11). The following

Hi, I was lately debugging parts of my 'colAUC' function in caTools package, and in a process looked into other packages for calculating Areas Under ROC Curves (AUC). To my surprise I found at least 6 other functions: * wilcox.test * AUC from ROC package, * performance from ROCR package, * auROC from limma package, * ROC from Epi package, * roc.area from verification

This workaround is taken from Linux, and the main motivation (besides such workarounds indeed belonging in the hypervisor rather than each kernel) is to suppress the warnings in the Xen log each Linux guest would cause due to the disallowed wrmsr. Signed-off-by: Jan Beulich <jbeulich@novell.com> --- a/xen/arch/x86/cpu/amd.c +++ b/xen/arch/x86/cpu/amd.c @@ -43,6 +43,47 @@ static inline void

I have a complex function that I want to maximize (I have multiplied this function by -1 so that it becomes a minimization problem in the code below). This function has two equality constraints. I get the programs to run but the answer isn't correct because, when it does converge, at least one of the constraints is violated. Any suggestions? Code below Violated constraint (an easy check):

I'm solving 4 complex equations simultaneously. Code is below. The code returns only zero's for the solution though there should also be a non-zero result. I'm pretty confident that the equations are correct because they are straight from a published paper and I checked them pretty thoroughly. The parameter values I used are from the published paper as well. Any suggestions for how

Estimados Usuarios-R: Estoy convirtiendo un programa en Matlab a R. El original lo saqu de: Lai, M., & Poltera, Y. (2009). Lecture with computer exercises: Modelling and simulating social systems with matlab. Tech. rep., Swiss Federal Institute of Technology (December 2009). 27. Ahora estoy convirtiendo la siguiente funcin: function sizes = gridsizes(N,varargin) % gridsizes(N) calculates

I've been attempting to understand the one-sample run test for randomness. I've found run.test{tseries} and run.test{lawstat}. Both use a large sample approximation for distribution of the total number of runs in a sample of n1 observations of one type and n2 observations of another type. I've been unable to find R code to generate the exact distribution and would like to see how

Hi, I'm doing a function that describe two populations in competition. that's the function that i wrote: exclusao<-function(n10, n20, k1, k2, alfa, beta, t){ n1<-k1-(alfa*n20) n2<-k2-(beta*n10) if(t==0){plot(t, n10, type='b', xlim=range(c(1:t),c (1:t)), ylim=range(n10, n20), xlab='tempo', ylab='tamanho populacional') points(t, n20, type='b',

Tried to post this last night, but it doesn't seem to have appeared. Using R 2.0.1 on Windows XP + SP2. I am traveling, away from my usual references. I'm trying to make a 4-dimensional plot: a levelplot with overlaid contours, with different response variables represented by (1) colors on the levelplot and (2) the contour lines. First try was filled.contour + contour but the key

Hello...i want to find the empirical rate for type 1 error using fixed trimmed mean. To make it easy, i'm referring to journal given by this website http://www.academicjournals.org/ajmcsr/PDF/pdf2011/Yusof%20et%20al.pdf. I already run the programme and there is no error in it but i got zero for the empirical rate of type 1 error. The empirical rate for the type 1 error given in the journal

Hi, Here are some new library functions for klibc. Some of them are required for udev, which currently has a klibc_fixups.c file that implements these functions. mh -- Martin Hicks Wild Open Source Inc. mort@wildopensource.com 613-266-2296 # This is a BitKeeper generated patch for the following project: # Project Name: The kernel C library # This patch format is intended

Hi, Erin: A cleaner way is to pass "n2" to "outer" as a "..." argument, as in the following modification of your code: boot1 <- function(y,method="f",p=1) { n1 <- length(y) n2 <- n1*p n3 <- n2 - 1 a <- 0.5*(outer(1:n3,1:n3,function(x,y, n2.){n2. - pmax(x,y)}, n2.=n2)) return(a) } y1 <- c( 9, 8, 7, 3, 6) boot1(y=y1,p=4)

By accident, I left out the lines defining n1 and n2. Here it is as a function. Peter B. hotelling <- function(d1,d2){ k <- ncol(d1) n1 <- nrow(d1) n2 <- nrow(d2) xbar1 <- apply(d1,2,mean) xbar2 <- apply(d2,2,mean) dbar <- xbar2-xbar1 v <- ((n1-1)*var(d1)+(n2-1)*var(d2))/(n1+n2-2) t2 <- n1*n2*dbar%*%solve(v)%*%dbar/(n1+n2) f <-

Hello, I haven't found errors in your code. I implemented the test in the paper (the first, fixed symetric mean) and it also gives me zero Type I errors, when alpha = 0.05. Try to see the value of min(pv) or to plot the histogram of 'pv', hist(pv) and you'll see that there are no significant p-values, at that level. Anyway I'll continue to look at it, but my first

Hi R-Developers, After my message about a month ago concerning attributes being lost during simple operations, Martin Maechler invited me to fix the code if I was in a hurry (especially for attributes in general). We've just made the following changes here, which appear to implement the rules in the Blue Book (pg. 257) Enclosed is the output from "diff -c" from /R-0.61.1/src

Hi I have a couple of functions that work on the object created by another R command and then print out or summarise the results of this work. The main function is defined as: hotelling.t <- function(obj) { #internal commands } I then have print.hotelling.t() that takes the list returned by hotelling.t and prints it with some extra significance calculations, formatting, etc. I want to

Thank you David. Using xtabs operation simplifies the code very much, many thanks ;) On Tue, Jun 6, 2017 at 7:44 AM, David Winsemius <dwinsemius at comcast.net> wrote: > > > On Jun 6, 2017, at 4:01 AM, Jim Lemon <drjimlemon at gmail.com> wrote: > > > > Hi Bogdan, > > Kinda messy, but: > > > > N <-