similar to: skewness and kurtosis in e1071 correct?

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

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

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

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

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

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"

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

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. --

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)))

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

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]

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 :

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 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 ==========================

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

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 <-

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")

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: