similar to: Skewness

I wonder whether the functions for skewness and kurtosis in the e1071 package are based on correct formulas. The functions in the package e1071 are: # -------------------------------------------- skewness <- function (x, na.rm = FALSE) { if (na.rm) x <- x[!is.na(x)] sum((x - mean(x))^3)/(length(x) * sd(x)^3) } # -------------------------------------------- and #

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 all, I wrote some user defined function for my own. Now I want to get a mechanism so that every time I start R, those function will automatically be loaded in R without manually copying pasting. Can gurus here pls tell me how to do that? Or I have to build my own packages bundled with those functions. However I am not familiar in writing R package yet. Regards, [[alternative HTML version

Hi, there is a function Skewness() under fBasics package. If I type "skewness", I get followings: > skewness function (x, ...) { UseMethod("skewness") } <environment: namespace:timeDate> Would be great if someone tell me how to see the codes of this function. 2ndly suppose I create following function: fn1 <- function(x) return(x+2) How

Can anyone explain such different output: > stableFit(s,alpha = 1.75, beta = 0, gamma = 1, delta = 0, + type = c("q", "mle"), doplot = TRUE, trace = FALSE, title = NULL, + description = NULL) Title: Stable Parameter Estimation Call: .qStableFit(x = x, doplot = doplot, title = title, description = description) Model: Student-t Distribution Estimated

Hi, in which R-package I could find skewness and kurtosis measures for a distribution? I built some functions: gamma1<-function(x) { m=mean(x) n=length(x) s=sqrt(var(x)) m3=sum((x-m)^3)/n g1=m3/(s^3) return(g1) } skewness<-function(x) { m=mean(x) me=median(x) s=sqrt(var(x)) sk=(m-me)/s return(sk) } bowley<-function(x) { q<-as.vector(quantile(x,prob=c(.25,.50,.75)))

> On Nov 1, 2017, at 12:51 PM, Tiby Kantrowitz <tlkantro at gmail.com> wrote: > > The prob package has been archived because it depends upon some other > packages which have issues. > > However, such projects as Introduction to Probability and Statistics in R > depend upon it for learning. There are a few other resources that also use > it. > > Does anyone

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 <-

> On Nov 2, 2017, at 11:15 AM, Tiby Kantrowitz <tlkantro at gmail.com> wrote: > > The issue is fAsianOptions. Is there a version that works with the latest version of R? If not, which version of it works with which version of R and where can it be found? I tried several at the archive already. sessionInfo() R version 3.4.2 Patched (2017-10-04 r73465) Platform:

When I try to load "fBasics" package, I get following error/warning : > library(fBasics) Loading required package: fImport Loading required package: fSeries Loading required package: fBasics Loading required package: fImport Loading required package: fSeries Loading required package: fBasics Loading required package: fImport Loading required package: fSeries Loading required package:

> On Nov 2, 2017, at 12:07 PM, Tiby Kantrowitz <tlkantro at gmail.com> wrote: > > Yes. That's the version I've been discussing that has non-zero exit status. That situation is why CRAN retired the prob package. It's possible you installed that library earlier in development and it's been "carried" along. It no longer installs, now. > > The problems

Dear R Users, Is anyone aware of a package which calculates the Yule Kendall resistant (to errors,outliers) measure of skewness ? An easy calculation to perform, but was just wondering if a package exists (as the contents of that package would probably include other cool things I would also be interested). Thanks, Tolga Generally, this communication is for informational purposes only and it

Hello everyone, Does anyone know what would cause the skewness() function (from e1071), as well as skew() from psych, to return a value of NaN? I have a vector of positively-skewed data (https://docs.google.com/file/d/0B6-m45Jvl3ZmYzlHRVRHRURzbVk/edit?usp=sharing) which these functions return a value for like normal: > skewness( data ) # returns 1.400405 but when I instead give those

The issue is fAsianOptions. Is there a version that works with the latest version of R? If not, which version of it works with which version of R and where can it be found? I tried several at the archive already. Alternatively, is there another package that behaves similarly to prob? On Wed, Nov 1, 2017 at 6:17 PM, David Winsemius <dwinsemius at comcast.net> wrote: > > > On Nov

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]

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. --

Yes. That's the version I've been discussing that has non-zero exit status. That situation is why CRAN retired the prob package. It's possible you installed that library earlier in development and it's been "carried" along. It no longer installs, now. The problems with all of this seem to have started this month according to the conversations. However, no one has

I have a question about the D'Agostino skewness test and the Anscombe-Glynn kurtosis test. agostino.test(x, alternative = c("two.sided", "less", "greater")) anscombe.test(x, alternative = c("two.sided", "less", "greater")) The option "alternative" in those two functions seems to be the null hypothesis. In the output, the

> On Nov 2, 2017, at 1:09 PM, Tiby Kantrowitz <tlkantro at gmail.com> wrote: > > Yes, that is exactly what I was doing two days ago. > > Warning in install.packages : > installation of package ?fAsianOptions_3010.79.tar.gz? had non-zero exit status > > Which is what a reading of the explanation for why "prob" was retired leads one to expect. Do you have

I fitted a gaussian mixture to my financial data. The data can be found here: http://uploadeasy.net/upload/32xzq.rar I look at the density with plot(density(dat),col="red",lwd=2) this has a skew of library(e1071) skewness(dat) -0.1284311 Now, I fit a gaussian mixture according to: f(l)=πϕ(l;μ1,σ21)+(1−π)ϕ(l;μ2,σ22) with: