similar to: Chi plot and Kendall plot

Somebody know what is the package in which I can find the association measures (like Kendall's Tau and Spearman's Rho) for a copula object (bivariate copulas)?? Thanks a lot. Marta Di Lascio __________________________________________________ [[alternative HTML version deleted]]

Hi r-users, I try to fit the t copula using the gamma marginals.  But I got error message which I don't really understand. Thank you for any help given. myCop.t <- ellipCopula(family = "t", dim = 2, dispstr = "toep", param = 0.5, df = 8) myCop.t myMvd <- mvdc(copula = myCop.t, margins = c("gamma", "gamma"), paramMargins = list(list(mean = 0, sd

> 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 r-users,   I really need help in fitting the t-copula.  I try to reproduce the example given by Jun Yan in “Enjoy the joy of copula” but I’m not sure how to correct the error based on the error message.  I tried so many ways but still could not get it working.   loglik.marg <- function(b, x) sum(dgamma(x, shape = b[1], scale = b[2], log = TRUE))   ctrl <- list(fnscale = -1)   #dat <-

Hi r-users, I really need help in fitting the t-copula. I try to reproduce the example given by Jun Yan in "Enjoy the joy of copula" but I'm not sure how to correct the error based on the error message. I tried so many ways but still could not get it working. loglik.marg <- function(b, x) sum(dgamma(x, shape = b[1], scale = b[2], log = TRUE)) ctrl <- list(fnscale

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)] >

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)

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

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

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]]

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",

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

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

Dear useRs, I've been trying to run a Mann-Kendall test in my data in order to detect trends. I studied the examples given at the Kendall package and I can understand pretty well how it works on time-series data. However, my data consists of values in different sites per year, as I display below;              Year 1 | Year 2 | Year 3 | ... Site 1        x           x          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

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 found some code to compute a Kendall-Theil slope estimate and want to add it to a scatter plot. Is there a way to make it appear like a regression fit instead of a line that extends from the edges of the plot? I would like to have the OLS appear as a dotted line and the KT a solid line but as it is the KT line is longer. -- View this message in context:

hi, i have 2 lists of ranks for which i'd like to compute kendall tau. there are ties in the ranks which (to the best of my knowledge) means i cant use tau a but rather b or c. how does R handle that? are ties automatically detected (using corr.test()) and is tau b/c computed instead of tau a? also kendall does not work when values in list 1 do not occur in list 2 (and vice versa) - how does

I got some R code that I don't understand. Question as comment in code //where is t comming from, what is phi inverse rAC <- function(name, n, d, theta){ #generic function for Archimedean copula simulation illegalpar <- switch(name, clayton = (theta < 0), gumbel = (theta < 1), frank = (theta < 0), BB9 = ((theta[1] < 1) | (theta[2] < 0)), GIG = ((theta[2] < 0) |

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