similar to: How to interpret Spearman Correlation

Hi, I am using color2D.matplot (...) function of "plotrix" package. I used a matrix of size around 20*20 However, apparently it failed to visualize the matrix and gave the following exception, which I don't have any idea about possible source of this error. "Error in plot.new() : figure margins too large" It would be appreciated if someone points me to the right origin

Hi, I would like to xor (bitwise) two matrices filled with binary values (0,1). The result of such XOR is expected to be 0,1. But apparently neither of xor nor bitXor is working in this case. I got ": binary operation on non-conformable arrays" error message when I used xor (M1,M2) . The problem with bitXor(M1,M2) is that it just truncates the result into a vector rather than a

Hello, I would be grateful if anybody can help me in finding an R function to compute weighted Spearman correlation coefficient? Kind regards, Daniel

Hallo! Is there an error in cor to calculate Spearman correlation with cor if there are NA's? cor.test gives the correct result. At least there is a difference. Or am I doing something wrong??? Does anybody know something about this? a<-c(2,4,3,NA) b<-c(4,1,2,3) cor(a, b, method="spearman", use="complete.obs") # -0.9819805 cor.test(a, b,

Dear all, I tried help.search("karber") and RSiteSearch("karber") and RSiteSearch("*karber*") to find whether the (trimmed) Spearman-Karber method for LD50 evaluation in toxicity data (e.g. according to Hamilton 1977) has been implemented in R. Or does this method feature under a different name? Of course logit and probit are doable, but Spearman-Karber seems to

Hi everyone, I've been trying to find a function that outputs the Pearson and/or Spearman correlation coefficients for several variables with the associated statistics in one single table/matrix. For what I've been able to understand the Stats package is only able to compute these coeficients/statistics only in defined pairs. This becomes time consuming when we want to determine these

Hallo, does anybody know if there is an implementation of the Spearman rank correlation in R that gives a correct (or at least 'safe') p-value in the case of ties?? I have browsed the R-help archives but I found nothing. Thanks a lot in advance for any help, Antonino Casile

Hello, I calculate the correlation between two matrices cor(x,y, method="spearman") and I am wondering if it possible to see only the significant correlations. I can do that for single OTUs with cor.test() command but I would like to have an output for whole matrix. Besides,I would like to plot the relative abundance of each OTU, against the number of significant pair-wise correlations

Dear R, I'm looking for exact p-values for Spearman's rank correlation in the presence of ties. This is available in StatXact and SPSS, but I haven't yet found it in R. Has anyone implemented this? -- Paul H Artes Assist Prof, Ophth Vis Sci Dalhousie University, QEII Eye Care Centre Halifax, NS, CANADA

Hello, Does anyone know if the cor function, when method = "spearman", returns a correlation coefficient corrected for any ties in the ranks of the data? I have data with quite a few ties and am thinking that I should use a calculation of the coefficient corrected for ties, but before I try and code this calculation myself, I thought I should check whether or not cor() automatically

Hi If I get a p-value less than 0.05 does that mean there is a significant relation between the 2 ranked lists? Sometimes I get a low correlation such as 0.3 or even 0.2 and the p-value is so low , such as 0.000001 , does that mean it is significant also? and would that be interpreted as significant low positive correlation or significant moderate positive correlation? Also,can R calculate the

> version _ platform i686-pc-linux-gnu arch i686 os linux-gnu system i686, linux-gnu status major 1 minor 8.1 year 2003 month 11 day 21 language R > cor( 1:3, rep(NA,3) ) # OK Error in cor(1:3, rep(NA, 3)) :

Dear R maintainers, R is great. Now that I have that out of the way, I believe I have encountered a bug, or at least an inconsistency, in how Spearman and Kendall rank correlations are handled. Specifically, cor() and cor.test() do not produce the same answer when the data contain NAs. cor() treats the NAs as data, while cor.test() eliminates them. The option use="complete.obs" has

vobolonkin at lic.co.nz wrote: > Full_Name: Vladimir Obolonkin > Version: tested in 2.0 to 2.4.1 > OS: linux, win, mac > Submission from: (NULL) (202.14.96.194) > > {{ Subject shortened manually -- to pass anti-spam filters > > Original-subject: Incorrect matrix of spearman correlations working \ > large (24000 by 425 and 78 by 425 data frames) in 64-bit Linux

Hi, I have just encountered a strange behaviour from 'cor' with regards to the treatment of NAs when calculating Spearman correlations. I guess it is a subtle bug. If I understand the help page correctly, the two modes 'complete.obs' and 'pairwise.complete.obs' specify how to deal with correlation coefficients when calculating a correlation _matrix_. When calculating

Hi all, Is there a convenient way to calculate Spearman correlation coefficients in R? Nick Nianqing Xiao, Ph.D NCI Center for Bioinformatics, NIH SAIC/Advanced Systems Group > 6116 EXECUTIVE BLVD 4026J > MSC 8335 > BETHESDA MD 20852 Phone: 301-451-6357 Fax: 301-480-4222 -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

hello help, i''ve searched through the manual pages and the only reference i can find to spearman rank correlation is cor.test, which only seems to give the significance value of the correlation. is there any way to get the actual value of rho? david. [[alternate HTML version deleted]]

cor.test and SuppDists give me different P-values for the same Spearman's rho. Which is correct, or am I doing something wrong? > x <- c(44.4, 45.9, 41.9, 53.3, 44.7, 44.1, 50.7, 45.2, 60.1) > y <- c( 2.6, 3.1, 2.5, 5.0, 3.6, 4.0, 5.2, 2.8, 3.8) > cor.test(x,y,method="spearman") Spearman's rank correlation rho data: x and y S = 48, p-value =

R-help(ers), Does anyone know of an R function available for calculating a confidence interval for a Spearman correlation? If no such resource is available, is using the confidence interval from a Pearson correlation a reasonable proxy if the vectors come from normal distributions (i.e. likely indistinguishable from the true confidence interval in error bars of an autocorrelogram or correlation

Dear HelpeRs, I have some data: "ice" <- structure(c(0.386, 0.374, 0.393, 0.425, 0.406, 0.344, 0.327, 0.288, 0.269, 0.256, 0.286, 0.298, 0.329, 0.318, 0.381, 0.381, 0.47, 0.443, 0.386, 0.342, 0.319, 0.307, 0.284, 0.326, 0.309, 0.359, 0.376, 0.416, 0.437, 0.548, 41, 56, 63, 68, 69, 65, 61, 47, 32, 24, 28, 26, 32, 40, 55, 63, 72, 72, 67, 60, 44, 40, 32, 27, 28, 33,