similar to: How to fit all points into plot?

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

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

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( +

I have a function XOLD() from a nearly verbatim port of legacy FORTRAN in a package. I have remplemented this function as XNEW() using much cleaner native R and built-in functions of R. I have switched the package to the XNEW(), but for historical reasons would like to retain the XOLD() somewhere in the package directory structure. An assertion through a README or other will point to

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]]

dear:teacher i have a problem which about the polr()(package "MASS"), if the response must have 3 or more levels? and how to fit the polr() to 2 levels? thank you. turly yours [[alternative HTML version deleted]]

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

Dear help-list members, I am a student at Durham University (UK) conducting a PhD on spatial representation in baboons. Currently, I'm analysing the effect of sampling interval on home range calculations. I have followed the baboons for 234 days in the field, each day is represented by about 1000 waypoints (x,y coordinates) recorded at irregular time intervals. Consecutive waypoints in

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,

Hello all, I have an optimization routine that is giving me good results, but the results are not in the nice "model" format like "lm". How can I get optim results into a model so that I can use the clever 'fitted', 'residuals', and 'summary' functions? Using optim is the only way that I was able to make a model that 1) sums the betas to 1, 2)

Dear R-helpers, I've been thinking about this for some time, maybe someone can help. I have a fairly large dataset with thousands of firms, call the a, b, c, etc.. such as [,1] [,2] [1,] "A" 0.5 [2,] "" 0.2 [3,] "" 0.3 [4,] "B" 0.1 [5,] "" 0.9 [6,] "C" 0.4 Or to put it differently two vectors such as y

Hi, I was hoping to clarify the exact behavior associated with this incantation: validate(fit.ols, method='cross', B=50) Output: index.orig training test optimism index.corrected n R-square 0.5612 0.5613 0.5171 0.0442 0.5170 50 MSE 1.3090 1.3086 1.3547 -0.0462 1.3552 50 Intercept 0.0000 0.0000 -0.0040 0.0040

Some of you may have seen the pythag() part in the R API definition in "Writing R Extensions" (source = doc/manual/R-exts.texinfo). or followed the report and Prof. Brian Ripley's answer about pythag()'s availability from R's binary. As we say in above manual >> `pythag(A, B)' computes `sqrt(A^2 + B^2)' without overflow or >> destructive

Hi, I was wondering if it is possible to get the rowindices without using the function "which" because I don't have a restriction criteria. Here's an example of what I mean: # take 10 randomly selected instances iris[sample(1:nrow(iris), 10),] # output Sepal.Length Sepal.Width Petal.Length Petal.Width Species 76 6.6 3.0 4.4 1.4

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

Hello, I would like to run a script in which a loop is included. Since I'm new to R, I cannot manage the following problem. I really hope someone could help me out. Data in the variable Y should be removed from the simulated data set with probability 0.50 if the variable X has a value below zero, and with probability 0.10 if X has a value above zero (see script). However, the total number of

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",

Dear all, how can I plot a line graph and a bar graph in one single figure? I tried to combine "barplot" and "plot". Even though they both have the same x-values (1 to 55),  it just doesnt look as if they match in their scale (the barplot is much wider than the "plot"....even though I tried to put limits on the x-axis). Here is an example of what I did:

Dear experts, I am a beginner of R. I'm looking for experts to guide me how to do programming in R in order to randomly replace 5 observations in X explanatory variable with outliers drawn from U(15,20) in sample size n=100. The replacement subject to y < 15. The ultimate goal of my study is to compare the std of y with and without the presence of outliers based on average of 1000