similar to: Spearman probabilities and SuppDists

I am experiencing strange (to me) output when trying to do simple calculations. Expressions that should equal zero yield non-zero values. Examples: > a <- 4.1-3.1 > b <- 5.1-4.1 > a-b [1] -4.440892e-16 > (4.1-3.1)-(5.1-4.1) [1] -4.440892e-16 When this last expression is expanded, I get the right answer: > 4.1-3.1-5.1+4.1 [1] 0 I am using the binary packaged version

Full_Name: David Simcha Version: 2.10 OS: Windows XP Home Submission from: (NULL) (173.3.208.5) > a <- c(1:10) > b <- c(1:10) > cor.test(a, b, method = "spearman", alternative = "greater", exact = TRUE) Spearman's rank correlation rho data: a and b S = 0, p-value < 2.2e-16 alternative hypothesis: true rho is greater than 0 sample estimates:

Hi, R! Question1: I am trying to correlate two vectors of numbers (two columns of microarray signal values) by using the non-parametric Spearman's rank correlation coefficient rho: > cor.test(V2.Signal,V3.Signal,method="spearman") but I get the error message: Error in if (q > (n^3 - n)/6) pspearman(q - 1, n, lower.tail = FALSE) else pspearman(q, : missing value

Full_Name: Jan T. Kim Version: 2.1.0 (and better) OS: Linux Submission from: (NULL) (139.222.3.229) The p value in Spearman's test is NA if the length of x exceeds 46340, due to an integer overflow, occurring if length(n) > sqrt(2^31): > n <- 46341; > set.seed(1); > x <- runif(n); > y <- runif(n); > cor.test(x, y, method =

There is an even simpler way: someone wrote n*(n^2-1) as n*(n-1)*(n+1) and caused the problem. Your superfluous semicolons do definitely make your code harder to read. On Tue, 23 Aug 2005 jtk at cmp.uea.ac.uk wrote: > Full_Name: Jan T. Kim > Version: 2.1.0 (and better) > OS: Linux > Submission from: (NULL) (139.222.3.229) > > > The p value in Spearman's test is NA if

Dear R developers: There is a possible bug in calculating the p-value for Spearman's rank correlation. Line 155 in file R-patched/src/library/stats/R/cor.test.R is as.double(round(q) + lower.tail), I think, it should be as.double(round(q) + 2*lower.tail), The reason is that round(q) is expected to be an even number (the S statistic), so the next feasible value is round(q)+2.

Hi, Is there a limit on the number of observations for using cor.test. For example, > library(ctest) > cor.test(rnorm(3000), rnorm(3000), method="spearman") Error in if (q > (n^3 - n)/6) pspearman(q - 1, n, lower.tail = FALSE) else pspearman(q, : missing value where logical needed In addition: Warning message: NAs introduced by coercion I mainly want to calculate

Full_Name: Petr Savicky Version: 2.7.2, 2.8.1, 2.9.0 OS: Linux Submission from: (NULL) (147.231.6.9) The p-value of Spearman's rank correlation test is calculated in cor.test(x, y, method="spearman") using algorithm AS 89. However, the way how AS 89 is used incures error, which may be an order of magnitude larger than the error of the original algorithm. The paper, which

Hi All: help(cor.test) claims For Spearman's test, p-values are computed using algorithm AS 89. Algorithm AS 89 was introduced by the paper D. J. Best & D. E. Roberts (1975), Algorithm AS 89: The Upper Tail Probabilities of Spearman's rho. Applied Statistics, Vol. 24, No. 3, 377-379. Table 1(a) in this paper presents maximum absolute error |\Delta_m|, of the approximation for

I have been unable to install the package RandomFields. I am using R 2.9.0-4 on Ubuntu 9.04. To install, I use the command: sudo R CMD INSTALL RandomFields_1.3.37.tar.gz The output follows below. Any help Would be appreciated. D. Hoysak Brandon University * Installing to library ?/usr/local/lib/R/site-library? * Installing *source* package ?RandomFields? ... ** libs g++

I have been unable to install the package RandomFields. I am using R 2.9.0-4 on Ubuntu 9.04. To install, I use the command: sudo R CMD INSTALL RandomFields_1.3.37.tar.gz The output follows below. Any help Would be appreciated. D. Hoysak Brandon University * Installing to library ?/usr/local/lib/R/site-library? * Installing *source* package ?RandomFields? ... ** libs g++

Hello, I wuold like to propose my modifications of the original cor.test to you : I tried to calcolate the correct p-value for Spearman and Kendall's test with ties. Let me know what you think. Thanks you for your time. Antonietta di Salvatore test <- function(x, ...) UseMethod("test") test.default <- function(x, y, alternative = c("two.sided",

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]]

Hello, I was trying to fit a Johnson curve by first figuring out the parameter estimates using JohosnFit of a vector by a group ID using the aggregate function. I.E. aggregate(x, by = list(ID), JohnsonFit) where x is the variable I am trying to perform JohnsonFit on. It is a continuous random variable. However, I keep getting the following error: Error in JohnsonFit(x) : Unbounded solution

Greetings. There seems to be a problem with the P-value computation in the cor.test with method="spearman". In R1.8.0 (MS Windows) I seem to be getting intermittently nonsense P-values, but the rho's are OK. I can get this reproducibly with the toy example attached where the first use is OK and subsequent calls with the same data give nonsense. (I have also seen the problem

Hello R gurus, I want to calculate the Spearman rho between two ranked lists. I am getting results with cor.test that differ in comparison to my own spearman function: > my.spearman function(l1, l2) { if(length(l1) != length(l2)) stop("lists must have same length") r1 <- rank(l1) r2 <- rank(l2) dsq <- sapply(r1-r2,function(x) x^2) 1 - ((6 * sum(dsq))

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

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,

Hi, I am not really familiar with Correlation foundations, although I read a lot. So maybe if someone kindly help me to interpret the following results. I had the following R commands: correlation <-cor( vector_CitationProximity , vector_Impact, method = "spearman", use="na.or.complete") cor_test<-cor.test(vector_CitationProximity, vector_Impact,

Hi. I am currently trying to run some Spearman correlations, and have encountered two issues. 1) When using cor.test() with a variable that includes ties, I get the "Cannot compute exact p-values with ties" error. I have read that this function now uses an asymptotic formula that allows for ties, so do not understand why I am getting this error. (I am running version 2.4.0.) I