similar to: skewness and kurtosis in e1071 correct? (correction)

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 #

Trying to select a subset of cases (rows of data) I encountered several problems: Firstly, because I did not read the help to read.spss() thoroughly enough, I treated the data read as a data frame. For example, dr2000 <- read.spss('myfile.sav') d <- subset(dr2000,RBINZ99 > 0) and thus received an error message (Object "RBINZ99" not found), because dr2000 is not a

After loading the package "Matrix" (version 0.995-12), using the summary function with an lme (package nlme version 3.1-75) object results in an error message saying Fehler in dim(x) : kein Slot des Namens "Dim" f?r dieses Objekt der Klasse "correlation" (translated: 'Error in dim(x) : no slot of the name "Dim" for this object of class

Just out of curiosity (and I hope that my question does not confuse those who intuitively understood the par(new=TRUE) statement right in the beginning): I would like to know whether beginners (learning R) had the same difficulty as I had: Intuitively I thought that par(new=TRUE) would draw a new plot (and not into an already existing plot) and that par(new=FALSE) would not draw a new plot

Using ranef() (package nlme, version 3.1-75) with an 'lme' object I can obtain random effects for intercept and slope of a certain level (say: 1) - this corresponds to (say level 1) "residuals" in MLWin. Maybe I'm mistaken here, but the results are identical. However, if I try to get the standardized random effects adding the paramter "standard=T" to the

I receive R-help messages in digest form that makes it difficult to answer a post. I noticed that my answer is not added to the thread (instead, a new thread is started) although I use the same subject line (starting with "Re: ") as the original post. Is there a solution (I prefer the digest to separate messages for several reasons and don't want to change my email reader)? The

Although I tried to find an answer in the manuals and archives, I cannot solve this (please excuse that my English and/or R programming skills are not good enough to state my problem more clearly): I want to write a function with an indeterminate (not pre-defined) number of arguments and think that I should use the "..." construct and the match.call() function. The goal is to write

Begin forwarded message: > Subject: R: Studdy Missing Data, differentiate between a percent > with in the valid answers and with in the different missing answers > take a look at the Website from Dirk Enzmann: > http://www2.jura.uni-hamburg.de/instkrim/kriminologie/Mitarbeiter/ > Enzmann/Software/Enzmann_Software.html > He provides a function called "freq.r" - maybe

I hesitate to post this question in the light of recent threads, indeed I have hesitated for several weeks, however I have come to a full stop and really need some help if I am going to progress. I am a new user of R for medical statistics. I have attempted to read all the relevant documents, but would welcome any suggestions as to what I have missed. I am trying to contruct "table 1"

The update of VR by downloading VR_7.1-6.zip and using install.packages (from local zip files) fails with the following error message: Error in file(file, "r") : unable to open connection In addition: Warning message: cannot open file `VR/DESCRIPTION' Other packages can be installed without problems, except of dse_2003.4-1 with a similar error message. Why? Operating System:

Is it possible to avoid the loop in the following function (or make the function otherwise more efficient) and can someone point me to a possible solution? (It would be great if hours could be reduced to seconds :-). # --------------------------------------------- RanEigen=function(items=x,cases=y,sample=z) { X=matrix(rnorm(cases*items),nrow=cases,byrow=F) S=crossprod(X-rep(1,cases) %*%

Can someone show me how to specify zero inflated poisson and zero inflated negative poisson models in R? I would like to replicate the example given in Long (1997: Regression Models for Categorical and Limited Dependent Variables) in Chapter 8.5 (pp. 242-247). TIA Dirk ************************************************* Dr. Dirk Enzmann Criminological Research Institute of Lower Saxony

Dear R-Help: As you can see, Prof. Friendly refers me to your site for an executable version of vcd. I don't mean to be obtuse, but 15 minutes spent exploring your site failed to locate a downloadable version of the vcd package to which he referred. I know plainly what this application can do. What I need to know is how to obtain the application itself. My thanks in advance for any

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. --

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 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

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 <-