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> library(Kendall) > Kendall(1:3,1:3) WARNING: Error exit, tauk2. IFAULT = 12 <<<<<< tau = 1, 2-sided pvalue =1 I believe Kendall tau is well-defined for this case and the reported value is correct; isn't it a bug to give a warning? (And if, e.g., the pvalue is not well-defined in this case, wouldn't it be better to return NA or NaN or something?) Also,

Hi, I try to calculate Kendall's W coefficient and I have a bizarre error. little.app.mat<-matrix(c(1,3,4,2,6,5,2,4,3,1,5,6,3,2,5,1,5,4),nrow=3,byrow=TRUE) print(kendall.w(little.app.mat[-1,])) >>> Kendall's W for ordinal data >>> W = 0.7753623Error in if (is.na(x$p.table)) { : argument is of length zero

Hello, I thougth that there is a function which does the kendall test in R, I writed on the console apropos("kendall") and I didn't found anything can you tell me how could I do to use the kendall test? Thanks. _____________________________________________________________________________ l [[alternative HTML version deleted]]

Hi every body: I need some help with kendall.global. The example in the manual seems not working well, and cannot used with my data, always the same error. data(mite) > mite.hel <- decostand(mite, "hel") > > # Reproduce the results shown in Table 2 of Legendre (2005), a single group > mite.small <- mite.hel[c(4,9,14,22,31,34,45,53,61,69),c(13:15,23)] >

Dear R users I want to compute Kendall's Tau between two vectors x and y. But x and y may have zeros in the same position(s) and I wrote the following function to be sure to drop out those "double zeros" "cor.kendall" <- function(x,y) { nox <- c() noy <- c() # for (i in 1:length(x)) if (x[i]!= 0 | y[i] != 0) nox[length(nox)+1]<- x[i] for (i in

Hi there, I'm trying to apply the Mann Kendall test for trend analysis of a time series. I have downloaded and installed the package Kendall and subsequently loaded it into the software. My time series is a .txt file with 2 columns - column 1 is the year (1985 - 2009) and column 2 is the corresponding entry variable. According to the R guidelines, the call should be: MannKendall(x)

I know this is a dumb question but I'm pulling out what little hair I have left. I download the package and got the following: trying URL ' http://ftp.ussg.iu.edu/CRAN/bin/windows/contrib/2.14/Kendall_2.2.zip' Content type 'application/zip' length 52732 bytes (51 Kb) opened URL downloaded 51 Kb package ‘Kendall’ successfully unpacked and MD5 sums checked The downloaded

Hi all, I would like to ask a question related to Kendall package. I ran Kendall (x,y) and saw the results. But I am not sure which tau values R reported. I have ties in my data set, so I want tau-b. Can anybody tell how Kendall package is calculating tau values? I have looked at the package PDF, but I could not find any useful information. As long as I see from the following link, there

Full_Name: Dirk Koschuetzki Version: 2.1.1 OS: source code Submission from: (NULL) (194.94.136.34) Hello, >From the source code (R-2.1.1, file: .../R-2.1.1/src/library/stats/R/) ****************************** cor.test.default <- function(x, y, alternative = c("two.sided", "less", "greater"), method = c("pearson", "kendall",

Dear R-helpers, I'm fighting with the following problem : I want to do bootstrapping on a Kendall correlation with the following code : > cor.function <- function(data,i) cor(data[i, 1], data[i, 2],method="kendall") > boot.ci <- boot.ci(boot.cor <- boot(cbind(x,y),cor.function, R=1000),conf=c(0.95,0.99)) However, I've got problems because I've got ties

Hello - does anyone know whether there are any packages for Mann-Kendall mutation tests in R available? The only one I could find online is this MK_mut_test: Mann-Kendall mutation test in Sibada/sibadaR: Sibada's accumulated R scripts for next probably use to avoid reinventing the wheel. (rdrr.io) <https://rdrr.io/github/Sibada/sibadaR/man/MK_mut_test.html> but there doesn't seem to

I've noticed that the implementation of Kendall's Tau in R is O(N^2). The following reference describes how it can be done in O(N log N): A Computer Method for Calculating Kendall's Tau with Ungrouped Data William R. Knight Journal of the American Statistical Association, Vol. 61, No. 314, Part 1 (Jun., 1966), pp. 436-439 http://www.jstor.org/pss/2282833 I'm interested in

Hi, I am running a correlation analysis on a temporal dataset. I was wondering if you would receive the same tau and p values running the function: MannKendall(x), where x is the dependant variable that changes with time as you would running: Kendall(d,x), where x is the exact same dataset as the x entered into MannKendall and d is the date on which the observation was made (assuming that

Hello, I can't find a package which calculates Kendall's tau-c. There is the package Kendall, but it only calcuates Kendall's tau-b. Here is the example from ttp://www2.chass.ncsu.edu/garson/pa765/assocordinal.htm. cityriots <- data.frame(citysize=c(1,1,2,2,3,3), riotsize=c(1,2,1,2,1,2), weight=c(4,2,2,3,0,4)) cityriots <- data.frame(lapply(cityriots,function(x)

Hi, I need to calculate Kendall's tau for large data vectors (length > 100'000). Is somebody aware of a faster algorithm or package function than "cor(, method="kendall")"? There are ties in the data to be considered (Kendall's tau-b). Any suggestions? Regards Ferdinand

Colleagues, I ran some nonparametric regressions in R (run in RedHat Linux), then a colleague repeated the analyses in SAS. When we obtained different results, I tested S-Plus (same Linux box). And, got yet different results. I replicated the results with a small dataset: DATA: 37.5 23 37.5 13 25 16 25 12 100 15 12.5 19 50 20 100 13 100 10 100 10 100 16 50 10 87.5

Hi all, I'm not quite sure if this is a feature or a bug or if I just fail to understand the documentation: If I use cor() with pairwise.complete.obs and method=pearson, the result is a scalar: ->cor(c(1,2,3),c(3,4,6),use="pairwise.complete.obs",method="pearson") [1] 0.9819805 The documentation says that " '"pairwise.complete.obs"' only

Hello. Has any further action been taken regarding implementing David Simcha's fast Kendall tau code (now found in the package pcaPP as cor.fk) into R-base? It is literally hundreds of times faster, although I am uncertain as to whether he wrote code for testing the significance of the parameter. The last mention I have seen of this was in 2010

A couple years ago, we moved to Oracle RAC on Linux using ocfs that is SAN attached to an EMC CLARiiON. At the time, there was a reason that we did NOT use EMC's Powerpath (I just can't recall what that reason was). What I'd like to know is if there are any issues with introducing Powerpath now. * RHEL 2.1 AS * 2.4.9-e.38enterprise * ocfs-2.4.9-e-enterprise-1.0.13-1 * EMC

Hi, I have the following two measurements stored in mat: > print(mat) [,1] [,2] [1,] -14.80976 -265.786 [2,] -14.92417 -54.724 [3,] -13.92087 -58.912 [4,] -9.11503 -115.580 [5,] -17.05970 -278.749 [6,] -25.23313 -219.513 [7,] -19.62465 -497.873 [8,] -13.92087 -659.486 [9,] -14.24629 -131.680 [10,] -20.81758 -604.961 [11,] -15.32194 -18.735 To calculate the ranking