similar to: alternative option in skewness and kurtosis tests?

Dear useRs, I was searching CRAN for implementation of kurtosis and skewness tests, and found that there is some kind of lack on it. So, I have written three functions: 1. Anscombe-Glynn test for kurtosis 2. Bonett-Seier test based on Geary's kurtosis (which is not widely known, but I was inspired by original paper describing it, found coincidentally in Elsevier database) 3.

Dear R-users, I am comparing differences in variance, skew, and kurtosis between two groups. For variance the comparison is easy: just var.test(group1, group2) I am using agostino.test() for skew, and anscombe.test() for kurtosis. However, I can't find an equivalent of the F.test or Mood.test for comparing kurtosis or skewness between two samples. Would the test just be a 1 df test on

Hello, I'd appreciate any ideas on how to compare the skewness of two samples. In my case, one sample is likely to be roughly normal and the other one skewed. I could run two D'Agostino tests, but then I'll have to correct for the family-wise error. What if both samples are skewed? If there are no general tests (or they can't exist), I'd like to know. Thanks, Skirmantas

Greetings, I have generated several ROC curves and would like to compare the AUCs. The data are cross sectional and the outcomes are binary. I am testing which of several models provide the best discrimination. Would it be most appropriate to report AUC with 95% CI's? I have been looking in to the "net reclassification improvement" (see below for reference) but thus far I can only

Hi, Does anyone know if the D'agostino test is available with R ? Alex

Hi, I am trying to calculate net reclassification improvement (NRI) and Inegrated Discrimination Improvement (IDI) for a survival dataset to compare 2 risk models. It seems that the improveProb() in Hmisc package does this only for binary outcome, while rcorrp.cens() does take survival object, but doesn't output NRI or IDI. Can anyone suggest any other packages that can calculate NRI and IDI

Hola Carlos. Muchas gracias. No es exactamente lo que estoy buscando (sería genial ver que alguien tiene un paquete con la prueba de Nam-D'Agostino) pero puedo aprovechar algo de código. Encontré alguna referencia al test de Gronnesby&Borgan en el paquete stcoxgof de Stata, pero estoy torpe para encontrar algo hecho en R (y me extraña que no haya nada) Un saludo, Miguel. De: Carlos

Hola. Una duda.... Alguien sabe si hay algo hecho en R para comprobar si un modelo de supervivencia está bien calibrado? (usando las pruebas de Nam-D'Agostino o de Gronnesby & Borgan). Thnks. Un Saludo, _____________________________ Miguel Ángel Rodríguez Muíños Dirección Xeral de Innovación e Xestión da Saúde Pública Consellería de Sanidade Xunta de Galicia http://dxsp.sergas.es

Hello, I am interested in looking at the dataset used by Stock and Watson in their "Macroeconomic Forecasting Using Diffusion Indexes (J. of Business and Econ. Statistics, April 2002, pp158-161) or the set used by D'Agostino and Giannone "Comparing Alternative Predictors [...]"(October 2006) in R. Does anyone know if the R-code to retrieve these series from FRED (as

A lo mejor si escribes a los que mantienen la Task-View de R (Survival Analysius) te pueden dar la clave...: CRAN Task View: Survival Analysis*Maintainer:*Arthur Allignol and Aurelien Latouche*Contact:*arthur.allignol at fdm.uni-freiburg.de*Version:*2013-08-09 Y en Stata, como referencia adicional (que puede conducir a algo equivalente en R): http://www.jstatsoft.org/v53/i12/paper Saludos,

Juraj17 wrote: > > Do I have to write my own, or it exists yet? How name has it, or how can I > use it. > Try the R-function search. It return the function you are looking for as the first match. Dieter -- View this message in context: http://r.789695.n4.nabble.com/D-Agostino-test-tp3424952p3425833.html Sent from the R help mailing list archive at Nabble.com.

Dear R users, I hope to explain the concepts of skewness and kurtosis by generating series of distributions with same skewness and different kurtosis or with same kurtosis and different skewness, but it seems that i cannot find the right functions. I have searched the mailing list, but no answers were found. Is it possible to do that in R? Which function could be used? Thanks a lot. --

I'm sorry, but my previous message, as often happens, some brackets were wrong: Here are the correct formulas: sd = 1/n * sum((x-mean(x))^2) # (1) sd = 1/(n-1) * sum((x-mean(x))^2) # (2) This also occured in the last paragraph. Dirk ************************************************* Dr. Dirk Enzmann Institute of Criminal Sciences Dept. of Criminology Edmund-Siemers-Allee 1 D-20146

Dear all, Right now, I'm doing research about outlier in statistical data (univariate and multivariate) and I want to simulate its behavior. My problem is : How to generate random data from distribution with zero skewness and some kurtosis values in R ? A. Kudus ===================== Dept. of Statistics Bandung Islamic University I n d o n e s i a ==========================

Thanks to all who response my problem. Here are my summary : 1. from Dirk Eddelbuettel <edd at debian.org> We could try a mixture of normals -- ie flip a coin (use a uniform with some cutoff c where 0 < c < 1 ) to choose between N(0, sigma_1) and N(0, sigma_2). 2. from Michaell Taylor <michaell.taylor at reis.com> We could use the gld library to specify the lambdas of

Hello everybody, this is a bit off topic, so maybe you can just reply to me personally... What is the typical notation for 'skewness', 'kurtosis' and maybe 'excess kurtosis'? Thank you, Martina -------------------------------------------------------------------------- Department of Statistics Office Phone: (614) 292-1567 1958 Neil Avenue, 304E Cockins Hall

Hello I wonder whether there is an r tool or package available for testing for the null of same skewness or kurtosis of two independent samples. It semes that nsRFA package uses L-moments for soothing similar but I could not get how to use the package for the above test. Any pointers, help, example and etc. will be most welcome. Many thanks Ed [[alternative HTML

I checked the help and the mailing list archives, but I can find no mention of a routine that calculates higher moments like skewness and kurtosis. Of course, these are easy enough to write myself, but I was thinking that they MUST be in here. Am I wrong? Thanks. -Frank

Dear R-Users and Developpers, Currently R does not include functions to compute the skewness and kurtosis. I programmed it myself in the following way, but probably *real* programmers/statisticians can do that better: mykurtosis <- function(x) { m4 <- mean((x-mean(x))^4) kurt <- m4/(sd(x)^4)-3 kurt } myskewness <- function(x) { m3 <- mean((x-mean(x))^3) skew <-

Is there some reasonable way to generate random data from a distribution that has some degree of skewness and/or kurtosis, but would otherwise be normal? thanks, -------------- next part -------------- A non-text attachment was scrubbed... Name: greiff.vcf Type: text/x-vcard Size: 398 bytes Desc: Card for Warren R. Greiff Url :