similar to: pivot algorithm

I am trying to implement the so called pivot algorithm for a markov chain monte carlo simulation of self avoiding random walks. There must be a simple method of checking to see if the pivoted portion of the random walk intersects with the previous section? In other words I have a list of adjacent coordinates divided into two parts. I apply an orthogonal transformation to one part and I need to

Hi to all, how could I to rotate automatically a data sheet which was imported by read.xls? x1 x2 x3 .... xn y1 1 4 7 ... xn/y1 y2 2 5 8 .... xn/y2 y3 3 6 9 ....xn/y2 yn ... ... ... Xn/Yn to y1 y2 y3 .... yn x1 1 2 3 ..... Yn/x1 x2 4 5 6 .... Yn/x2 x3 7 8 9 .... Yn/x2 xn ... ... ... ..... Yn/xn Kind regards Knut

From: xxgreat@hotmail.com To: r-help-bounces@r-project.org Subject: compare a vector and a row of a matrix Date: Sun, 26 Sep 2010 23:23:52 +0800 Hi Everyone: I am trying to compare a vector and rows of a matrix for example > xn <- c(1,2,4,4,5,5,5,6) >yn <- c(1,2,5,7,1,2,3,1) >mtrx <- cbind(xn, yn) when I tried, say, > c (1,4), the result was TRUE, TRUE.

I have now committed a version "fulfilling" your wish, partly at least, to R-devel . In the new approx(*, na.rm=FALSE) cases, the result of how NA's are treated does depend on the 4 different extrapolation rules {1, 2, 1:2, 2:1} The main reason was that I kept the low level code in C to do +- what it did before which automatically was using 'rule' to determine these

Full_Name: Jonathan Lees Version: 1.8.1 OS: GNU/Linux 2.4.20-20.8smp #1 SMP Submission from: (NULL) (152.2.75.114) I am having trouble with the postscript output of images. They have lines on them that are not supposed to be there. I have noticed this on numerous trials of printing various images. I looked at the postscript and I see that it appears to plot each individual block - so perhaps

Hi everybody, Suppose I have continuous measurements of an energy waveform that is sampled discretely for different heights every 0.5m. Let's say I want to find out the height for which I have equal amount of energy above and below. My colleague did the following: a. calculate the cumulative sum of the energy b. calculate the median of the cumulative energy c. find out what is the height

Hi Sherri, There are examples of topographic maps which you have been pointed to, however, I suspect that you want to know where you can obtain topographic data from rather than a canned example. There are quite a few intricacies to the process so I will go through them for you. (1) Topography files can be found in the geomapdata library. You will probably want to use the maps package too (if

Hi all, I am currently compiling R to RISC-V64 CPU and I think I have discovered a NA propagation failure. How R implements NA (not available) and NaN (not-a-number) is explained in detail here: https://stat.ethz.ch/pipermail/r-devel/2014-February/068380.html. In short, according to my understanding of R's convention, any calculation involving NA but no NaN should result in NA (called NA

Hi, This might seem like a simple question but at the moment I am stuck for ideas. The columns of my matrix in which some data is stored are of this form: X1 Y1 X2 Y2 X3 Y3 ... Xn Yn with n~100. I would like to look at just the X values (i.e. odd column numbers). Is there an easy way to loop round extracting only these columns? Any help would be appreciated.

suppose I have two sets of vectors: x1,x2,...,xN and y1,y2,...,yN. I want N correlations: cor(x1,y1), cor(x2,y2), ..., cor(xN,yN). my sets of vectors are arranged as data frames x & y (vector=column): x <- data.frame(a=rnorm(10),b=rnorm(10),c=rnorm(10)) y <- data.frame(d=rnorm(10),e=rnorm(10),f=rnorm(10)) cor(x,y) returns a _matrix_ of all pairwise correlations: cor(x,y)

Dear all, I have two coordinates vectors, say X and Y of length n. I want to generate for each couple of coordinates X1,Y1 X2,Y2 X3,Y3....Xn,Yn a random coordinate which is located in a square define as X +/- dx and Y +/- dy. I saw the runif function which can generate for just one value at a time what I want : runif(1, X - dx, X + dx) for X and runif(1, Y - dy, Y + dy) for Y. I would like

This is a covariance calculation question so nothing to do with R but maybe someone could help me anyway. Suppose, I have two random variables X and Y whose means are both known to be zero and I want to get an estimate of their covariance. I have n sample pairs (X1,Y1) (X2,Y2) . . . . . (Xn,Yn) , so that the covariance estimate is clearly 1/n *(sum from i = 1 to n of ( X_i*Y_i) ) But,

Dear R-users, I've been using R for a while and I am very satisfied! Unfortunately, I still have not figured out an efficient and general way to construct and use lags of time series, especially when I need to work with different packages. Let me give an example. I have two time series x and y and I want to estimate a variaty of distributed lags models and run different tests

Hi all, Are there functions in R that could help me do the following? We have a special type of regression which is called Geometric Mean Regression. We have done some search and found the following: https://stat.ethz.ch/pipermail/r-help/2011-July/285022.html The question is: how to do the statistical inference on GMR results? More specifically, we are looking for the prediction interval:

Hello, Can anyone give me some suggestion in term of calculating the sum below. Is there a function in R that can help doing it faster? x1, x2, ...xn where xi can be 0 or 1. I want to calculate the following: sum{ beta[a+sum(xi), b+n-sum(xi) ]* [ (1-x1)dnorm(0,1)+x1dnorm(2,1) ]* [ (1-x2)dnorm(0,1)+x2dnorm(2,1) ]* ...* [ (1-xn)dnorm(0,1)+xndnorm(2,1) ] } The sum in the beginning is over all

Dear all, I'm having problems installing the colorspace package on Red Hat Enterprise Linux 5: * Installing *source* package 'colorspace' ... ** libs gcc -std=gnu99 -I/usr/lib/R/include -I/usr/lib/R/include -I/usr/local/include -fpic -O2 -g -pipe -Wall -Wp,-D_FORTIFY_SOURCE=2 -fexceptions -fstack-protector --param=ssp-buffer-size=4 -m32 -march=i386 -mtune=generic

Hi, I am attempting to write code which will read in my data which is of this form: X1 Y1 X2 Y2 .... Xn Yn 0 0 0 0 0 0 1 0 1 255 1 0 2 255 2 0 2 255 3 0 3 0

I am trying to automatically construct a distance function from a training set in order to use it to cluster another data set. The variables are nominal. One variable is a "class" variable having two values; it is kept separate from the others. I have a method which constructs a distance matrix for the levels of a nominal variable in the context of the other variables. I want to

I have 3 vectors x,y,z: x<-c(-2.88,-1.92,-.96,0,.96,1.92,2.88,3.84, -1.92,-.96,0,.96,1.92,2.88,3.84, -.96,0,.96,1.92,2.88,3.84, 0,.96,1.92,2.88,3.84, .96,1.92,2.88,3.84, 1.92,2.88,3.84, 2.88,3.84, 3.84) y<-c(rep(-3.84,8), rep(-2.88,7), rep(-1.92,6), rep(-.96,5), rep(0,4), rep(.96,3), rep(1.92,2), 2.88) z<-c(.65,1.78,2.4,2.54,3.04,2.22,2.97,3.56, .745,1.287,1.98,1.91,2.02,2.24,2.95,

Dear Masters, first I'd like to wish u all a great 2011 and happy holydays by now, second (here it come the boring stuff) I have a question to which I hope u would answer: I run a logistic regression by glm(), on the following data type (y1=1,x1=x1); (y2=0,x2=x2);......(yn=0,xn=xn), where the response (y) is abinary outcome on 0,1 amd x is any explanatory variable (continuous or not)