similar to: SLLN for loggamma fails for 2 order moments

UseRs, actuar is a package for Actuarial Science. A rather preliminary version (0.1-3) of the package has been available on CRAN since February 2006. We now announce the immediate availability of version 0.9-2 sporting a large number of new features. Non actuaries behold! There can be some features of interest for you, especially those related to new probability distribution and to the

UseRs, actuar is a package for Actuarial Science. A rather preliminary version (0.1-3) of the package has been available on CRAN since February 2006. We now announce the immediate availability of version 0.9-2 sporting a large number of new features. Non actuaries behold! There can be some features of interest for you, especially those related to new probability distribution and to the

Hello. I am not certain even how to search the archives for this particular question, so if there is an obvious answer, please smack me with a large halibut and send me to the URLs. I have been experimenting with fitting curves by using both maximum likelihood and maximum spacing estimation techniques. Originally, I have been writing distribution-specific functions in 'R' which work

Hello please note that the code at https://stat.ethz.ch/pipermail/r-help/2006-August/110892.html to compute indices of skewness and kurtosis for the skew-t distribution is not correct. It has been kindly pointed out that i made some error in this code, which was a bit too quickly copied from the paper. The 'sn' package already contains a facility for computing the cumulants, namely

Dear R helpers If for a given data, I need to calculate Mean, Standard Deviation, Mode, Median, Skewness, Kurtosis, is there any package in R, which will calculate these moments? Individually I can calculate these, but if there is any function which will calculate these at a stretch, please let me know. Maithili The INTERNET now has a personality. YOURS! See your Yahoo! Homepage.

hello users of the SN package, i thought i post here some useful help on R code on the 4 moments for the skew t sampling gives seldom good results for skewness and kurtosis, so one really needs the analytical results, it took me some time to get it from the article Azzalini, A. & Capitanio, A. (2003), Distributions generated by perturbation of symmetry with emphasis on a multivariate

Hi all, I'm wondering whether it is possible to construct a confidence interval using only the mean, variance, skewness and kurtosis, i.e. without any of the population? If anyone could help with this it'd be much appreciated (even if just a confirmation of it being impossible!). Thanks. -- View this message in context:

1) L-moments: Does anyone know of any R code that will calculate these? (I'm aware that these can be calculated in S-Plus using the EnvironmentalStats for S-Plus module.) 2) Hosking & Wallis (1997): "Regional frequency analysis: an approach based on L-moments" Does anyone know of any code in either R or S-plus that implements the discordancy and homogeneity methods described

We have just released PC Moments - 'The PC Pioneers Lite' - this has selected the 100 most important PC Moments that we believe contributed to deliver the PC and the Net as we know them today - and the 400 PC Pioneers who delivered them. See it at wikiPCpedia.com or contact bobd at thePCpioneers.com -- If you wish to unsubscribe press here

hi all does anyone know how one would calculate the covariance matrix of a vector of estimated parameters if we use the method of moments technique? one could use bootstrapping techniques but there should be some asymptotic results that could be used as per MLE estimates. a reference would be much appreciated.

Hi everyone, In the package POT, there is a function that computes the L-moments of a given sample (samlmu). However, to compute those L-moments, one needs to obtain the total number of combinations between two numbers, which, by the way, requires the use of a factorial. See, for example, Hosking (1990 , p. 113). How does the function "samlmu" in the package POT avoids overflows? I

Dear Experts, If I have a vector of numbers x. (1) How can I write R code to compute the moments around zero of order one to four? (2) How can I write R code to compute the moments around the mean of order one to four? Thank you very much! -- View this message in context: http://r.789695.n4.nabble.com/Writing-R-code-for-moments-tp2967946p2967946.html Sent from the R help mailing list archive

Hello, I know that Mclust does the fitting on its own but I am trying to implement an optimization with the aim to generate a the mixture gaussian with the combine moments as closed as possible to the moment of my return distribution. The objective is to Min Abs((Mean Ret - MeanFit)/Mean Fit) + Abs((Std Ret -Stdev Fit)/Stdev) + Abs((Sk Ret-Sk fit)/Sk Fit) + Abs((Kurt Ret- Kurt Fit)) Taking

How to adapt this piece of code but for: - gamma distribution - 3 parameter log normal More specifically, where can I find the specification of the parameter (lmom) for pelgam() and pelln3()? Lmom package info just gives: pelgam(lmom), lelln3(lmom), where lmom is a numeric vector containing the L-moments of the distribution or of a data sample. # Draw an L-moment ratio diagram and add a line for

Hi all! I'm sure this is a stupid question but I can't find an answer. How can I fit the Gumbel distribution to my data using The Method of Moments in R? Thank you for helping me, Tonja

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

https://bugs.freedesktop.org/show_bug.cgi?id=106334 Bug ID: 106334 Summary: Freeze of system at random moments (using Wayland) Product: xorg Version: unspecified Hardware: Other OS: All Status: NEW Severity: normal Priority: medium Component: Driver/nouveau Assignee: nouveau

Hello I do not know very much about statistics (and English language too :-( ), then I come in search of a clarification (explanation): I found two distinct results on KURTOSIS and I do not know which of them is the correct one. Any aid will be welcome! klebyn ################ CODE rnorm(1000) -> x library(moments) kurtosis(x) skewness(x) detach("package:moments")

Hi, I'm a newcomer to R, having previously used SPSS. One problem I have run into is computing kurtosis. A test dataset is here: http://www.whinlatter.ukfsn.org/2401.dat > library(moments) > data <- read.table("2401.dat", header=T) > attach(data) > loglen <- log10(Length) With SPSS, I get Skewness -0.320 Kurtosis -1.138 With R: > skewness(loglen) [1]

Hi! Suppose I have a dataset as follows pd = c(10,7,10,11,7,11,7,6,8,3,12,7,7,10,10) I wish to calculate the mean, standard deviation, median, skewness and kurtosis i.e. regular standard statistical measures. average = mean(pd) stdev    = sd(pd) median = median(pd) skew    = skewness(pd) kurt     =  kurtosis(pd) Q. No (1) How do I get these at a stretch using some R package? I came across