similar to: filter data set unique, duplicate..

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

Hi. Maybe this is a stupid question. If so, I apologize, but here goes. Suppose I have a function f1(x,...) that calls a function f2(y1,y2,...,yn) in the following way: if x satisfies a certain condition, then I want to call f2(x,y2,...,yn); otherwise I want to use the default value of y1, if there is one. I could do something like the following: v <- ifelse ( is.null(x), f2( , y2,...,

Hi I have a dataframe, RQ, like this: A B1 B2 B3 1 NA 112 12 2 NA 123 123 3 NA 324 13 4 3 21 535 5 4 12 33 6 7 1 335 7 4 NA 3535 8 4 NA NA 9 NA NA NA 10 5 NA NA 12 4 NA NA 15 2 NA NA 17 3 NA 1 63 1 NA 1 75 NA NA NA 100 NA NA NA 123 NA NA

I have a set of data in the form x1, y1, z1 x1, y2, z2 ... x1, yN, zN x2, y1, z(N+1) x2, y2, z(N+2) ... x2, yN, z(2N) ...and so on... xM, yN, val(M*N) I have been trying to figure out how to get R to use this data in a persp plot. So far the only thing that I can figure out to do is to break the data file into three different files. The first file contains the x-coordinate data: x1 x2

Hi, I have multiple responses y1, y2, .., yn, and would like to do linear regression for each of them with x1, x2, ..., xm. Instead of doing regression n times, it it possible to do it all at once? I tried lm(y1+y2 ~ x1 + x2 + x3) and lm added y1 y2 and then did the regression. thanks Jeff

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)

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.

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

Hello R, I have data in txt file of n columns like this: x y1 .....yn 1 100 2 50 3 10 4 200 5 20 I need to find coordinates for each maxima e.g.: [x,y1],[x,y2]...[x,yn] a=read.table() attach(a) b=y1<-x max(b) returns only value of y but no corresponding x value -- View this message in context:

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,

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

Hello, I have a doubt about the plotting position of the theoretical quantile for the qqnorm command in R. Let F be the theoretical distribution of Y, we observed a sample of size n, y1,y2, ..., yn. We then sort it and comspare these empirical quantiles to the expected ones from F. For the plotting poition, there are several options: 1. i/(n+1) 2. (i-.375)/(n+.25) 3. (i- .3175)/ (n + .365) etc.

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:

Dear All, I would like to plot a scalar (e.g. a temperature) on a non-rectangular domain (or even better: I would simply like to be able to draw a contour plot on an arbitrary 2D domain). I wonder if there is any tool to achieve that with R. I did some online search in particular on the list archives, found several queries similar to this one but was not able to find any conclusive answer. I

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

Hi, I'm trying to extract a histogram over the results from a bootstrap. However I keep receiving the error message "Error in hist.default(boot.lrtest$ll, breaks = "scott") : 'x' must be numeric". The bootstrap I'm running looks like: > boot.test <- function(data, indeces, maxit=20) { + y1 <- fit1+e1[indeces] + mod1 <- glm(y1 ~ X1-1, maxit=maxit) +

Hola. Como hago para calcular la "Maxima Verosimilitud" de unos datos con distribucion uniforme? saludos. -- Leo [[alternative HTML version deleted]]

Hi! When I force-resync a mailbox of mine, I see following output: # doveadm force-resync -u $USER $PATH doveadm($USER): Warning: mdbox .../storage: Inconsistency in map index ($X,$Y2 != $X,$Y2) doveadm($USER): Warning: fscking index file .../storage/dovecot.map.index doveadm($USER): Warning: mdbox .../storage: rebuilding indexes doveadm($USER): Error: mdbox .../storage: Duplicate GUID $G in

Dear all, I wonder if there are some function or package in R which can do the iterative proportional fitting. In the exponential model f(y1,...yn)=exp(a'yi+b'(yi*yj)+.....+c'(y1*...*yn)+constance), instead of the canonical parameters, I use maginal probability instead of a and log odds ratio instead of b. and for the order higher than 3, I use the canonical way or even assume

I'm running samba 2.2.8a on a redhat 9 box, everything works great, but ever since I playd with the system-auth I now have to enter a password in twice when I logon to the console. Any one got any ideas ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Iwan Davies Server Support and Development Technician Cyngor Sir Ceredigion County Council IT Section Finance iwandav@ceredigion.gov.uk