similar to: Is there a statistics that can summarize the correlation for more than two random variables?

This seems more like a STATS question than an R question - asking on a list like STAT-L or ALLSTAT may result in more replies Nevertheless, it seems to me that you need to describe (and maybe decide) what you mean by 'summarize' the correlations. Certainly the mean DOES summarize them, but is it the summary you want? Maybe, maybe not. Perhaps the median? Or a trimmed mean? Do you want

Hi all, I'd like to use the Hmisc::summarize function, but it uses a function (FUN) of a single vector argument to create the statistical summaries. Consider an easy case: I'd like to compute the correlation between two variables in my dataframe, grouped according to other variables in the same dataframe. For exemple, consider the following dataframe D: V1 V2 V3 A 1 -1 A 1

This is not an R question but if anyone can help me, it's much appreciated. Suppose I have a series ( stationary ) y_t and a series x_t ( stationary )and x_t has variance sigma^2_x and epsilon is normal (0, sigma^2_epsilon ) and the two series have the relation y_t = Beta*x_t + epsilon My question is if there are particular values that sigma^2_x and sigma^2_epsilon have to take in

Dear R users, Does the results below make any sense? Can the the interval of the correlation coefficient be between *-1.0185* and -0.8265 at 95% confidence level? Liviu > library(boot) > data(mtcars) > with(mtcars, cor.test(mpg, wt, met="spearman")) Spearman's rank correlation rho data: mpg and wt S = 10292, p-value = 1.488e-11 alternative hypothesis: true rho is not

hi everyone, Suppose I have three variables a, b, and c each with 10 values. Now I construct a corr matrix for them. Now I want to give the names of columns of corr matrix as a, b, c, i.e. the first column of corr matrix will have name as ‘a’ second column with ‘b’ and so on. Can anyone give me any code by which I can automatically assign the names of columns of corr matrix which are

I've a vector of pairwise correlations in the order low-index element precedes the high-index element, say: corr(1,2)=0.1, corr(1,3)=0.2, corr(2,3)=0.3, corr(3,4)=0.4 How can I construct the corresponding correlation matrix? I tried using the "combn"-function in "combinat" package: library(combinat) combn(c(0.1,0.2,0.3,0.4),2) , but to no avail... Thank you for your

Given a square matrix of variables X, is there any way to compute a multivariable correlation among all the variables in the array? It is possible to calculate the correlation of all pairs of variables in the array, but I want to know the correlation of all the variables taken together, i.e. for the matrix X=x1 x2 x3 x4 x5 x6 x7 x8 x9 I don't want the pair-wise correlations

Hi R users, I have one simple question but I really don't know why I can't get it work. The data was adopted from Efron's An introduction to the bootstrap book. > nlaw LSAT GPA [1,] 576 3.39 [2,] 635 3.30 [3,] 558 2.81 [4,] 578 3.03 [5,] 666 3.44 [6,] 580 3.07 [7,] 555 3.00 [8,] 661 3.43 [9,] 651 3.36 [10,] 605 3.13 [11,] 653 3.12 [12,] 575 2.74

Hi, Being a R-newbie I am wondering how to calculate a correlation coefficient (preferably with an associated p-value) for data like: > d[,1] [1] 25.5 25.3 25.1 NA 23.3 21.5 23.8 23.2 24.2 22.7 27.6 24.2 ... > d[,2] [1] 0.0 11.1 0.0 NA 0.0 10.1 10.6 9.5 0.0 57.9 0.0 0.0 ... Apparently corr(d) from the boot-library fails with NAs in the data, also cor.test cannot cope with a

Hi Folks, I'm analysing some data which, in its simplest aspect, has 3 factors A, B, C each at 2 levels. If I do lm1 <- lm(y ~ A*B) say, and then summary(lm1, corr=T) I get the correlation matrix of the estimated coeffcients with numerical values for the correlations (3 coeffs in this case). Likewise with 'glm' instead of 'lm'. However, if I do lm2 <- lm(y ~

Hi, Seeking suggestions to compute uncentered (pearson correlation) correlation efficiently. corr from stats library works on x and y columns. dist from amap library works on x and y rows. My data layout is slightly different such that row(i) of matrix x is compared to row(i) of matrix y. Thanks [[alternative HTML version deleted]]

I have a large correlation matrix that I'm trying to convert to a list of every connection (edge) between every two nodes with its accompanying correlation value (for Cytoscape). I figured out how to do this and to remove the connections that nodes have to themselves but I can't figure out how to get rid of the duplicate pairs (e.g. the edge b-a is a duplicate of a-b).

Dear R people, I have a very big tab-delim txt file with header and I only want to import several columns into R. I checked the options for "read.table" and only found "nrows" which lets you specify the maximum number of rows to read in. Although I can use some text editors (e.g., wordpad) to edit the txt file first before running R, I feel it?s not very convenient. The

Dear Listers: I used cronbach{psy} to evaluate the internal consistency and some set of variables gave me alpha=-1.1003, while other, alpha=-0.2; alpha=0.89; and so on. I am interested in knowing how to interpret 1. negative value 2. negative value less than -1. I also want to re-mention my previous question about how to evaluate the consistency of a set of variables and about the total

All, I have a repeated measures data frame and was wondering if the covariance matrix can be calculated via some created indexing or built-in R function. Specifically, say there are 3 variables, where potassium concentration is measured 6 times on each patient. Patient number (discrete) Time (1 to 6, discrete) Potassium (continuous variable) I want the covariance/correlation matrix for the

Dear All, I have a data frame with n columns: X1, X2, ., Xn. Now I want to create a new column: if X1 = X2 = . = Xn, the value is 1; Otherwise, the value is 0. How to do that in a quick way instead of doing (n choose 2) comparisons? Thank you, Frank [[alternative HTML version deleted]]

veepsirtt wrote: > > corr <- cor(s1,s2) > Error in cor(s1, s2) : incompatible dimensions > > Check lenghts of your series. cor(c(1,2),c(1,2,3)) #Error in cor(c(1, 2), c(1, 2, 3)) : incompatible dimensions Dieter -- View this message in context: http://r.789695.n4.nabble.com/Finding-the-correlation-coefficient-of-two-stocks-tp3246992p3247042.html Sent from the R help

Hello, I am having a problem specifying the correlation structure in lme which leads to the error: Error in getCovariate.corSpatial(object, data = data) : Cannot have zero distances in "corSpatial". I have specified a grouping variable which is the only fix I could find by searching this error on R-help. ISee the below example. When my samples (tran) - which are transects

Hi I have used a polycor package for categorical correlation coefficients. I run the following script. But there were no results. Could you tell me how to correct the script? Thanks in advance, vars <- names(sdi) for (i in 1:length(vars)) { for (j in 1:length(vars)) { paste(vars[i]," and ", vars[j]) polychor(vars[i], vars[j]) # corr } } -- Kum-Hoe Hwang, Ph.D.Phone :

Hi guys I have an input file with multiple columns and and rows. Is it possible to calculate correlation of certain value of certain No (For example x of S1 = 112) with all other values (for example start with x 112 corr a 3 of S1 = x-a 0.2 ) INPUT ******* No S1 S2 S3 S4 Sn a 3 4 45 34 23 x 112 0 12 23 0 b 0 1 23 12 1 n 0 1 0 1 1