similar to: Package design, placement of legacy functions

Dear Experts, The following is my "Iterator". When I try to write a new function with itel, I got error. This is what I have: > supDist<-function(x,y) return(max(abs(x-y))) > > myIterator <- function(xinit,f,data=NULL,eps=1e-6,itmax=5,verbose=FALSE) { + xold<-xinit + itel<-0 + repeat { + xnew<-f(xold,data) + if (verbose) { + cat( +

Dear Researchers, I wrote two function to fit a circle using noisy data. 1- the fitCircle() is derived from MATLAB code of * zhak Bucher* from the link http://www.mathworks.com/matlabcentral/fileexchange/5557-circle-fit/content/circfit.m 2- the CircleFitByPratt() from MATLAB code of *Nikolai Chernov *from the link

Hi, I have a problem when I want to add new points (or a new line) to the graph. Some points (or parts of the line) are not shown on the graph because they lie beyond the scale of the axis. Is there a way to overcome this so all points (or the entire line) are shown on the graph? Here's an example of my problem: colors = c("red", "blue") plot(x=rnorm(100,0,1),

Dear colleagues Please could someone kindly explain the following inconsistencies I've discovered when performing logical calculations in R: 8.8 - 7.8 > 1 > TRUE 8.3 - 7.3 > 1 > TRUE Thank you, Emma Jane [[alternative HTML version deleted]]

Hi I am having difficulty defining an S4 method for head() and tail(). I can't quite provide minimal self-contained code because the problem appears to require the whole corpus of my package; and there also appears to be a difference between sourcing the lines directly, and having them installed in a package. The lines in question (I think) are: setClass("mdm",

Hello everyone. R-2.12.0, suse linux 11.3. I am debugging a package that uses S4 methods and R CMD check gives the following warning: > Warning in methods::findMethods(g, env) : > non-generic function 'mdm' given to findMethods() > See the information on DESCRIPTION files in the chapter 'Creating R > packages' of the 'Writing R Extensions' manual. I

I am porting some FORTRAN to R in which an Inf triggers an if(). The trigger is infinite on exp(lgamma(OVER)). What is the canonical R style of determining OVER when exp(OVER)== Inf? The code structure that I am porting is best left intact--so I need to query R somehow to the value of OVER that causes exp(lgamma(OVER)) to equal Inf. On my system, exp(lgamma(171)) is about first to equal Inf.

Hi, Could someone please suggest where I might find some instructions / tutorials / FAQs that describe how to create a frequency distribution and cumulative frequency distribution in R using different class withs. I have about a 2-million observations (distances between points ranging from sub-millimetre to about 400km, and I want to get a feel for how they are distributed). I'd like the

Dear all, I wanna to do multiple comparison test for proportions (multiple chi squre ?), could someone tell me how in R, thank you!

Hi everyone, I've been having difficulty writing wrapper functions for some functions where those same functions include other functions with eval() calls where the environment is specified. A very simple example using function lmer from lme4: lmerWrapper <- function(formula, data, family = gaussian, method = c("REML", "ML", "PQL", "Laplace",

Folks, I'm doing fine with using orthogonal polynomials in a regression context: # We will deal with noisy data from the d.g.p. y = sin(x) + e x <- seq(0, 3.141592654, length.out=20) y <- sin(x) + 0.1*rnorm(10) d <- lm(y ~ poly(x, 4)) plot(x, y, type="l"); lines(x, d$fitted.values, col="blue") # Fits great! all.equal(as.numeric(d$coefficients[1] + m

Hi, I am trying to write a function to automate multiple graph generation. My data looks like: Table of numeric values with the following headers: timeM1 statusM1 xM1 timeM2 statusM2 xM2 timeM3 statusM3 xM3 1 2 3 4 5 6 Where M1,M2, M3 hve no similarity except they have a max string length of 7. Examples are mcw0045, adl0003, lei0101. Now, what I want to do is Function(M1, M2,

Hello. I am trying to write an S4 method for rbind(). I have a class of objects called 'mdm', and I want to be able to rbind() them to one another. I do not want the method for rbind() to coerce anything to an mdm object. I want rbind(x1,x2,x1,x2) to work as expected [ie rbind() should take any number of arguments]. This is what I have so far: setGeneric(".rbind_pair",

CRAN et al., I would like to add an extented introduction or other arbitrary sections to my package lmomco. I have been shipping inst/doc/Introduction.Rd. I would like to have this content inserted to the front of the PDF build for the CRAN. The R-exts.pdf seems to be a little silent on this subject? For my purposes, I have been doing this R CMD Rd2dvi --pdf

This may sound like a very naive question, but... give two lists of coordinate pairs (x,y - Cartesian space) is there any simple way to compute the affine transformation matrix in R. I have a set of data which is offset from where i know it should be. I have coordinates of the current data, and matching coordinates of where the data should be. I need to compute the composition of the affine

Hey there, I apologize if this is an irritatingly simple question ... I'm a new user. I can't understand why R flips the sign of all data values when reading in external text files (tab delimited or csv) with the read.delim or read.csv functions. The signs of data values also seem to be flipped after assigning a new data.frame from within R (xnew <-- edit(data.frame()). What am

I have question (curiosity) regarding returned values of R's qcauchy () function, for nonexceedance probability (F). It seems the ideal returned range of cauchy distribution should be [-Inf,Inf]. For F=0 > qcauchy(0) [1] -Inf but for F=1 > qcauchy(1) [1] 8.16562e+15 It seems to me that the proper return value should be Inf??? For default (location=0,scale=1) quantile function of

Hello everybody, I'm a new user of R and I'm working right now with the ACE function from the acepack library. I Have a question: Is there a way to predict new responses using ACE? What I mean is doing something similar to the following code that uses PPR (Projection Pursuit Regression): library(MASS) x <- runif(20, 0, 1) xnew <- runif(2000, 0, 1) y <- sin(x) a <- ppr(x, y,

Hi, I'd appreciate help with this. I have a data matrix with one column, called f in the example below, a factor. I'd like to subtract the means from each of other columns for each level of the factor. That is, in the example, to go from the first matrix below to the second. I know SWEEP will take out means, but I want to do this for each level of the factor. f x 1 2 1

I think that this is an easy one... I have a matrix where each row is an (x,y,z) triplet. Given a potential (xnew,ynew,znew) triplet I want to know if the matrix already contains a row with the new values (the space already has that point). I can do it using a for loop, but I would like to know if there is anyway in which I can do it without the for loop. I do it now like this (this