similar to: how to do multiple responses in a linear regression

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,...,

Hello First, thanks for the help for an earlier question about error handling! I have problem filtering a dataset. I'm trying to filter the data in the y columns based on the values in the x column, e.g.: x y1 y2 yn 1.0 1 NA 3 2.0 1 NA 11 2.0 2 NA NA 3.0

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

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

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.

Hi, I have created a matrix and initially all elements in the matrix was assigned to NA.Then I want to assign values to some elements of this matrix. Can I use formation like matrix[i][j] <- 4?if not, how can i do this? now I have three vectors y1 y2 y3 3 4 3.1 5 2 4.2 if I want to assign y3's value to matrix, where the value's row and column should correspond the

Hi, Is there a way to get the enclosing function name within a function? For example, I would like to have a function getEnclosingFunctionName(). It works like below f = function(){ print(getEnclosingFunctionName()) } f() # will print "f" Thanks Jeff

Hi, I would like to extract the last row of each group in a data frame. The data frame is as follows Name Value A 1 A 2 A 3 B 4 B 8 C 2 D 3 I would like to get a data frame as Name Value A 3 B 8 C 2 D 3 Thank you for your suggestions in advance Jeff

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

Hello! I have a set of data of the form (x, y1, y2) where x is the independent variable and (y1, y2) is the response pair. The model is some messy non-linear function: (y1, y2) = f(x; param1, param2, ..., paramk) + (y1error, y2error) where the parameters param1, ..., paramk are to be estimated, and I'll assume the errors to be normal for sake of simplicity. If there were only one

Hi, I have a a vector and a data frame with two columns vec = c("C", "A", "B") dataDF = data.frame(A1 = c("B", "A", "C"), A2 = c(1,2,3)) I would like to sort the data frame by column A1 such that the order of elements in A1 is as the same as in vec. After the ordering, the data frame would be A1 A2 C

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

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

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.

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 there, I am new to using regression in R. I wanted to solve a simple regression problem where I have 2 equations and 2 unknowns. So lets say - y1 = alpha1*A + beta1*B y2 = alpha2*A + beta2*B y1 <- runif(100000, 0,1) y2 <- runif(100000,0,1) alpha1 <- 0.6 alpha2 <- 0.75 beta1 <- 1-alpha1 beta2 <- 1-apha2 I now want this equation to estimate the values of A and B. Both A