similar to: off-topic: affine transformation matrix

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 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( +

Hi, I have developed a logistic regression model in the form of (factor_1~ numeric + factor_2) and would like to perform a cross-validation or some similar form of sensitivity analysis on this model. using cv.glm() from the boot package: # dataframe from which model was built in 'z' # model is called 'm_geo.lrm' # as suggested in the man page for a binomial model: cost <-

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

Greetings, Experimenting with the cluster package, and am starting to scratch my head in regards to the *best* way to standardize my data. Both functions can pre-standardize columns in a dataframe. according to the manual: Measurements are standardized for each variable (column), by subtracting the variable's mean value and dividing by the variable's mean absolute deviation. This

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

Greetings: As I am not a windows user, I cannot try this: is it possible to install rgdal on windows without having to compile it from source ? Compilation on MacOS is within my abilities, however each time i try and install the rgdal package it dies complaining that it cannot find gdal-config --- which was recently installed with GRASS. I have updated my PATH environment variable, logged

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]]

Greetings, I am trying to add an extra labled axis in position 3 (top x-axis), with numbers that do not match up with the existing axes. Surely this must be possible, and I am just doing it incorectly. So far I have tried the following: #make a plot plot(TIK, type="l", cex=.25, xlim=c(2,32), ylim=c(0,1600)) #try and add a new axis with different numbers in position 3

Greetings, I have had good success using the clara() function to perform a simple cluster analysis on a large dataset (1 million+ records with 9 variables). Since the clara function is a wrapper to pam(), which will accept known medoid data - I am wondering if this too is possible with clara() ... The documentation does not suggest that this is possible. Essentially I am trying to

Greetings: are there any simple ways to convert an sp class object to a splancs ppp class object, outside of reading the coordinates and computing a bounding box? cheers, -- Dylan Beaudette Soils and Biogeochemistry Graduate Group University of California at Davis 530.754.7341

Greetings, I am using both the lrm() {Design} and glm( , family=binomial()) to perform a a logisitic regression in R. Apart from the typical summary() methods, what other methods of diagnosing logistic regression models does R provide? i.e. plotting an 'lm' object, etc. Secondly, is there any facility to calculate the R^{2)_{L} as suggested by Menard in "Applied Logistic

Hi everyone, Suppose I have a count the occurrences of positive results, and the total number of occurrences: pos <- 14 total <- 15 testing that the proportion of positive occurrences is greater than 0.5 gives a p-value and confidence interval: prop.test( pos, total, p=0.5, alternative='greater') 1-sample proportions test with continuity correction data: 14 out of

Getting a very strange error with a new install of R from source on x86; make[3]: Leaving directory `/tmp/R.INSTALL.r20887/cluster/src' ** R ** data ** moving datasets to lazyload DB Error in factor(c(1, 2, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1), : invalid labels; length 2 should be 1 or 1 Execution halted ERROR: lazydata failed for package 'cluster' ** Removing

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]]

Greetings, I have two matrices, read in from raster data stored in GRASS. Each matrix represents the output of a aggregation process on categorical data (Nomial / Ordinal) - derived from imagery. I have compared these two data by the following methods: ***** pretending the data is continuous approaches (flawed i am sure...) 1. computing a difference map by computing the absolute difference

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

Greetings, After pouring over the documentation for the 'colorspace' package, I have not been able to figure out how the plot() method converts colorspace coordinates to RGB values for display on the screen. I am convert between colorspaces with the various as() methods... but cannot seem to find a way to extract RGB (i.e. for displaying on a computer screen) triplets from color space

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

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