similar to: Concordance and Kendall's tau in copula

Thanks Dimitris!!! That's much clearer now. Still have a lot of work to do this weekend to understand every bit but your code will prove very useful. Cheers, Aziz -----Original Message----- From: Dimitrios Rizopoulos [mailto:Dimitris.Rizopoulos at med.kuleuven.be] Sent: May 12, 2006 4:35 PM To: Chaouch, Aziz Subject: RE: [R] Maximum likelihood estimate of bivariate

Full_Name: Dan Field Version: 1.6.2 OS: N/A Submission from: (NULL) (209.115.168.187) In kendall.c (library is ctest), the limits for the first loop in routine kendall_tau run from 0 through n-1, and the inner loop runs from 0 through i-1. This causes the each pair at index i to be compared with itself; my understanding is that there should only be n*(n-1)/2 pairs under consideration for

I have 3 variables relating to the successful introductions of species to 95 different areas: introduction frequency; number of successes pre 1906; number of successes post 1906 The data are not normal, nor homo-skedatic, so I am using non-parametric statistics. I have calculated Kendall's tau between both introduction & successes pre 1906 (tau=0.3903) and introduction & successes

I discovered that the Kendall's tau calculation in R uses all pairwise comparisons which is O(n^2) and takes a long time for large vectors. I implemented a O(n*log(n)) algorithm based on merge-sort. Is this of interest to be included in core R? The code (fortran and R wrapper) is available in my package clinfun v0.9.7 (not exported in NAMESPACE). Thanks, Venkat -- Venkatraman E. Seshan,

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

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

Full_Name: Marek Ancukiewicz Version: 2.10.1 OS: Linux Submission from: (NULL) (74.0.49.2) Both cor() and cor.test() incorrectly handle ordered variables with method="kendall", cor() incorrectly handles ordered variables for method="spearman" (method="person" always works correctly, while method="spearman" works for cor.test, but not for cor()). In

A search of the archives did not reveal an answer: For basic tests of association, where one has no a priori knowledge of the form of the relation or of the distributions of the variables, rank correlation seems like a good start. Why is cor.test() with Kendall and Spearman options relegated to the ctest package, rather than in the base package? Does this suggest that the developers consider

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

Hi all, I am going to sample two variables from two exponential distributions, but I want to specify a covariance structure between these two variables. Is there any way to do it in R? Or is there a "Multivariate Exponential" thing corresponding to the multivariate normal? Thanks in advance. Sincerely, Yanwei Zhang Department of Actuarial Research and Modeling Munich Re America Tel:

Hi all, Many thank in advance for helping me.? I tried to fit Expectation Maximization algorithm for mixture data. I must used one of numerical method to maximize my function. I built my code but I do not know how to make the optim function run over a different value of the parameters.? That is, For E-step I need to get the value of mixture weights based on the current (initial) values of

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

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 am trying to do a fit a loglikelihood function with Multivariate distribution via copulas with fitMdvc. The problem is that it doesn't recognize that my beta is a vector of km parameter and when I try to run it it say that the length of my initial values is not the same as the parameter. Can somebody guide me where my mistake is. Thanks, Elisa. #################################

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 All, I'm now working on Archimedean copulas and try to test the goodness of fit. Which packages I should use? I have Clayton copula with parameter (5.35) and Frank (19.5). I found this build function wrote by Yan and Ivan via R Packages, but I'm not sure the matrix for x? Please advice. e.g gofCopula(claytonCopula(1),x) Thank you Regards, Fayyad [[alternative HTML version

Greetings, I'm interested in generating data from various bivariate or mulitivariate distributions (e.g. gamma, t, etc), where I can specify the parameter values, including the correlations among the variables. I haven't been able to dig anything up on the faq, but I probably missed something. A nudge in the right direction would be appreciated. David --

Dear all, As I said in my previous email I have just upgraded to R 2.14.0 on Windows 7. I have just run the 'coxph' function and notice that a Concordance statistic is produced. Is there any way to extract this information from the output? E.g. can I call the concordance value independently of calling the output? Many thanks, Laura [[alternative HTML version deleted]]

Hello group, my question is deciding what test would be appropriate for following question. An experiment 'A' yielded 3200 observations of which 431 are significant. Similarly, using same method, another experiment 'B' on a different population yielded 2541 observations of which 260 are significant. There are 180 observations that are common between significant observations of A