similar to: Finding the correlation coefficient of two stocks

Sir, How to get the closing price from this link http://www.google.com/finance/historical?q=NSE:RCOM I installed quantmod getSymbols('NSE:RCOM',src='google') gives me this error********************** Error in download.file(paste(google.URL, "q=", Symbols.name, "&startdate=", : cannot open URL

Hi, based on the sample size I want to calculate whether to correlation coefficients are significantly different or not. I know that as a first step both coefficients have to be converted to z values using fisher's z transformation. I have done this already but I dont know how to further proceed from there. unlike for correlation coefficients I know that the difference for z values is

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 :

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

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

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, 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, 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]]

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

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 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 ~

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

Hi, I would like to obtain correlation parameters (e.g., coefficients, p-value) for multiple samples in regard to a reference. I have my data in a table with the reference as the second row (first row are headers) and then each sample in a row. What I do so far is load up the data, get the reference sample and use "apply" and "lm" to do the regression: x <-

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).

Hi, R people, I wonder if there is a statistics than can measure the correlation for more than two random variables, instead of computing the correlation coefficient matrix. If so, what R package should I use? Right now I can only think of the mean of all pair-wise correlation coefficients, e.g., (corr(x,y) + corr(x,z) + corr(y,z)) / 3 for three random variables (x, y, z). Thanks a

Dear all I apologize for cross-posting, but first it is accepted custom to thank the repliers and give a summary, and second I have still the feeling that this problem might be a general statistical problem and not necessarily related to microarrays only, but I might be wrong. First, I want to thank Robert Gentleman, Mark Kimpel and Mark Reiners for their kind replies. Robert Gentleman kindly

Dear list, I have 9 repeated measures (measurement variable == 'Delta13C') for individuals (ID variable == 'Individual_ID'. Each repeated measure is "indexed" (right term?) by the variable 'FeatherPosition' and given as c('P1', 'P2', 'P3', 'P4', 'P5', 'P6', 'P7', 'P8', 'P9'). I would like to

Hi there! In my case, cor(d[1:20]) makes me a good correlation matrix. Now I'd like to have it one sided, means only the left bottom side to be printed (the others are the same) and I'd like to have * where the p-value is lower than 0.05 and ** lower than 0.01. How can I do this? And another thing: Is there a way to output that table as a latex table? Thanks, Martin -- Ihr

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 list, I'd like to use path.analysis in the package agricolae in batch format on many files, retrieving the path coefficients for each run and appending them to a table. I don't see any posts in the help files about this package or the path.analysis package. I've tried creating an object out of the call to path.analysis, but no matter what I try, the function automatically prints