similar to: Help in R

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

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)

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.

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, 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 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

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

Hi everyone! I'm matching two samples to create one sample that have pairs of observations equal for the k1 variable. Merge() doesn't work because I dont't want to recycle the values. x <- data.frame(k1=c(1,1,2,3,3,5), k2=c(20,21,22,23,24,25)) x y <- data.frame(k1=c(1,1,2,2,3,4,5,5), k2=c(10,11,12,13,14,15,16,17)) y merge(x,y,by="k1") k1 k2.x k2.y 1 1 20

Hello, could You please help: I am looking for a way to formulate test accuracy measures such as test sensitivity, specificity, predictive values, and correct classification rate using p/d/qnorm. The tests' primary values follow a bimodal distribution, which is modelled by a mixture of two normal distributions: p * dnorm ((x - u1) / s1) / s1 + (1 - p) * dnorm ((x - u2) / s2) / s2)

>>>>> Robert Almgren >>>>> on Fri, 3 May 2019 15:45:44 -0400 writes [ __ to R-help __ -- here diverted to R-devel on purpose] > There is something I do not think is right in the approx() > function in base R, with method="constant" and in the > presence of NA values. I have 3.6.0, but the behavior > seems to be the same in

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, 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 posted before recently about fitting 3D data x, y, z where all have error attached. I want to predict z from x and y; something like z = b0 + b1*x + b2*y But multiple regression is not suitable because all of x, y, and z have errors. I have plotted a 3D scatterplot of some data using rgl. I see that the data form a cigar-shaped cloud. I think multiple regression is only suitable when the points

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 Folks, I've just come across a kind of problem which leads me to wonder how to approach it in R. Basically, each a set of items is subjected to a series of "impacts" until it eventually "fails". The "force" of each impact would depend on covariates X,Y say; but as a result of preceding impacts an item would be expected to have a "cumulative

Hi guys, I'm trying to use the the integral function to estimate the area under a PDF and a crossing curve. first I stated the function with several vectors in it: fn=function(a,b,F,mu,alpha,xi) { x<-vector() fs<-function(x) { c <- (mu+(alpha*(1-(1-F)^xi)/xi)) tmp <- (1 + (xi * (x - mu))/alpha) ((as.numeric(tmp > 0) * (tmp^(-1/xi - 1) *

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 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'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

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