similar to: add diagonal line

Dear all, I generated a covariance matrix and I would like to generate a 1D plot of the data that auto-correlate. any suggestions? Thanks, Marcelo -- Marcelo Andrade de Lima UNIFESP - Universidade Federal de São Paulo Departamento de Bioquímica Disciplina de Biologia Molecular Rua Três de Maio 100, 4 andar - Vila Clementino, 04044-020 Lab +55 11 55764438 R.1188 Cell +55 11 92725274

Hello, I'm trying to write the following matlab code into R: N = zeros(n-1); for i=2:(n-1) N(1,i) = 1/(pi * (i-1)); end for i=2:(n-2) for j=i:(n-1) N(i,j) = N(i-1,j-1); end; end for i=2:(n-1) end for j=1:i N(i,j) = -N(j,i); end; any suggestions? Thanks can i just add the following line to my calculation N=1/(pi*(i-1) -- Marcelo Andrade de Lima UNIFESP - Universidade Federal

Hi, Created a covariance matrix and i would like to add a diagonal line to the plot, any suggestions? Thanks -- Marcelo Andrade de Lima UNIFESP - Universidade Federal de São Paulo Departamento de Bioquímica Disciplina de Biologia Molecular Rua Três de Maio 100, 4 andar - Vila Clementino, 04044-020 Lab +55 11 55764438 R.1188 Cell +55 11 92725274 mlima@unifesp.br [[alternative HTML version

Dear List I just downloaded and installed R 2.12.0 and then installed R Commander . First it got RCmdr and Car, and then suggested for other packages for utilizing the full functionality- I clicked yes! I got 140 packages installed!!! Cran Mirror was UCLA... Here is the list. Is this intentional- I can see some packages like snow and multicore which are desirable but quite optional.(see list

Hello I can construct a correlation matrix from an (ordered) vector of correlation coefficients as follows: x <- c(0.1,0.2,0.3,0.4,0.5) n <- length(x) cmat <- diag(rep(0.5,n)) cmat[lower.tri(cmat,diag=0)] <- x cmat <- cmat+t(cmat) But how to do the reverse operation, i.e. produce x from cmat? Thanks for help, Serguei Kaniovski [[alternative HTML version deleted]]

Hello All, I have a data frame (dput information below) with food item weight for fish species. I need to calculate the Mean proportion by weight of each food item for each specie, as show in solution data frame (dput information below). I use the ddply function (plyr package) in two steps. First calculate the proportion of weight for each individual: step1 = ddply (example, .(ID), transform,

printCoefmat(signif.legend =FALSE) does not work properly. The option "signif.legend = FALSE" is ignored as shown in the example below. cmat <- cbind(rnorm(3, 10), sqrt(rchisq(3, 12))) cmat <- cbind(cmat, cmat[,1]/cmat[,2]) cmat <- cbind(cmat, 2*pnorm(-cmat[,3])) colnames(cmat) <- c("Estimate", "Std.Err", "Z value", "Pr(>z)") #

I try to code the ULS factor analysis descrbied in ftp://ftp.spss.com/pub/spss/statistics/spss/algorithms/ factor.pdf # see PP5-6 factanal.fit.uls <- function(cmat, factors, start=NULL, lower = 0.005, control = NULL, ...) { FAfn <- function(Psi, S, q) { Sstar <- S - diag(Psi) E <- eigen(Sstar, symmetric = TRUE, only.values = TRUE) e <- E$values[-(1:q)] e <-

Hi, In the data below, "case" represents cases, "x" binary states. Each "case" has exactly 9 "x", ie is a binary vector of length 9. There are 2^9=512 possible combinations of binary states in a given "case", ie 512 possible vectors. I generate these in the order of the decimals the vectors represent, as:

My data looks like this: > data name G_hat_0_0 G_hat_1_0 G_hat_2_0 G_0 G_hat_0_1 G_hat_1_1 G_hat_2_1 G_1 1 rs0 0.488000 0.448625 0.063375 1 0.480875 0.454500 0.064625 1 2 rs1 0.002375 0.955375 0.042250 1 0.000000 0.062875 0.937125 2 3 rs2 0.050375 0.835875 0.113750 1 0.877250 0.115875 0.006875 0 4 rs3 0.000000 0.074750 0.925250 2 0.897750 0.102000

Dear All, I have a correlation matrix of size 100 x 100 and would like to extract the diagonal matrix from it. I have used the for loop to store tha correlation values of the diagonal matrix. Is there a 'R way' of doing this? Thanks in advance. Kind regards, Ezhil

Hi, I have a correlation matrix of about 3000 items, i.e., a 3000*3000 matrix. For each of the 3000 items, I want to get the top 50 items that have the highest correlation with it (excluding itself) and generate a data frame with 3 columns like ("ID", "ID2", "cor"), where ID is those 3000 items each repeat 50 times, and ID2 is the top 50 correlated items with ID,

I've been playing around with contrasts in lm by specifying the contrasts argument. So, I want to specify a specific contrast to be tested Say: > y _ rnorm(100) > x _ cut(rnorm(100, mean=y, sd=0.25),c(-3,-1.5,0,1.5,3)) > reg _ lm(y ~ x, contrasts=list(x=c(1,0,0,-1))) > coef(reg)[2] x1 -1.814101 I was surprised to see that I get a different estimate for the

I have a model (run with glm) that has a factor, type. Type has two levels, "general" and "regional". I am trying to get estimates (and SEs) for the model with type="general" and type ="regional" using fit.contrast but I can't get the syntax of the coefficients to use in fit.contrast correct. I hope someone can show me how to use fit.contrast, or some

In a package I've been developing for manipulating genetic data I discovered a problem when indexing into character arrays using NA's: Create a character matrix and a numeric matrix > cmat <- matrix( letters[1:4], ncol=2, nrow=2) > nmat <- matrix( 1:4, ncol=2, nrow=2) Create an index vector containing an NA value > indvec <- c(1,2,NA) Indexing works fine for both

Hi! I am a bit new to R. I am looking for the right function to use for a multiple regression problem of the form: y = c1 + x1 + (c2 * x2) - (c3 * x3) Where c1, c2, and c3 are the desired regression coefficients that are subject to the following constraints: 0.0 < c2 < 1.0, and 0.0 < c3 < 1.0 y, x1, x2, and x3 are observed data. I have a total of 6 rows of data in a data set. Is

Hi Can anybody please suggest me about the documentation of "factanal.fit.mle()" (Not factanal()------ searching factanal.fit.mle() in R always leads to factanal()). Is there any function for doing principal component factor analysis in R. Regards Souvik Bandyopadhyay JRF, Dept Of Statistics Calcutta University [[alternative HTML version deleted]]

Hello. I'm not a regular subscriber in this mailing list, but I think that this announce may interest somebody. Please, forgive me if this is the wrong place. Based on the code of RSPython, but modifying it a little, I wrote an interface for using R from Python. The main reason for writing it was to make it robust, in order to avoid segmentation faults. Also, it is (IMMO) a very

I want to know how to get trace of product of matrices **faster** when the matrices are really big. Unfortunately the matrices are not symmetric. If anybody know how to get the trace of it, please help me. An example is as below. n <- 2500 a <- matrix(rnorm(n*n),n,n) b <- matrix(rnorm(n*n),n,n) tr1 <- sum(diag(a %*% b)) tr2 <- sum(diag(a %*% b %*% a %*% b)) Thanks, Yongwan Chun

Dear lme and lmer -ers, I have some problems using "home-made" contrast matrix in lme and lmer. I did an experiment to investigate the relationship between the response of an animal and some factors, namely the light wavelength (WA), the light intensity to which this animal was exposed and the sex of the animal tested. - The response can be a variable LA (normal distribution) or