similar to: Estimation of skewness from quantiles of near-normal distribution

Let's say I have a data.frame like A B C TS other columns 1 1 1 12345 1 1 1 56789 1 2 1 23456 1 2 2 23457 2 4 7 23458 2 4 7 34567 2 4 7 45678 and I want the last row for each unique combination of A/B/C, where by "last" I mean greatest TS. A B C TS other columns 1 1 1 56789 1 2 1 23456 1 2 2 23457 2 4 7 45678 I did this simply in SAS: proc sort data=DF; by A B C descending TS

I reproduce from memory my exhaustive look into this issue. RODBC uses the Microsoft ODBC DLL's developed by Microsoft. These DLL's perform an automatic determination of column type based on the contents of the first N rows of cells in each column, where N [0,16]. N may be set in the Windows system registry, and there are a few other things that may be set in the system registry which

I want to do the following: DEVw=500 DEVh=350 fname="my_plot" dev.print(file=fname, device=FOO, width=DEVw, height=DEVh, bg="transparent") How do I do this such that I can specify FOO to be one of several choices? (GDD, PNG, postscript, etc.) If I make FOO a character variable, then "dev.print" complains. I tried a simpled "substitute" but

Yes: I have Tufte's monograph on my desk. (along with 4 statistics texts) Yes: I am not the biggest fan of PowerPoint. Yes: I am using R to generate charts, plots, trends, etc. I have to summarize them each week. When I consider how to organize this data my first thought is to generate an HTML file with links to the R-generated plots, which HTML file organizes the plots in the required

Hi, I've been doing an experiment, measuring the dead-zone-diameters of bacteria, when they've been grown with paper diffusion disks of antimicrobial. There are two groups, or treatments - one is bacteria that have been cultured in said antimicrobial for the past year, the other group is of the same species, but lab stock and has not gone had any prior contact with the antimicrobial.

violating.runs I read from the news cran.r-project.org/doc/Rnews/Rnews_2004-1.pdf that the criteria for the violating is 5 but 1)I cannot find "5" in the code of the function. Where is the "5" ? 2)What is the easiest way to change it ? 3)Is there any more criterias made somewhere ? Yours sincerelly, Tommi Viitanen

I searched the archives and did not find a solution, so I pose this question to those well-versed in the use of plotmath and expressions. I have a list of strings in an external CSV file which I wish to use sometimes as plot axis labels and sometimes as plot titles. These strings combine plaintext and a few mathematical expressions (Greek letters, subscripts). Moreover, I sometimes need to

Madams & Sirs, I am working on porting some R code to one of our servers to run under web or crontab direction. With that in mind I have been working on directing informative, warning, and error messages to outputs as I require. I would like to suggest a change to the "warnings" function; that the passed arguments be enabled to all instances of "cat" in the function,

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

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 <-

I am a beginner in R, so please don't step on me if this is too simple. I have two data sets datax and datay for which I created a qqplot qqplot(datax,datay) but now I want a line that indicates the perfect match so that I can see how much the plot diverts from the ideal. This ideal however is not normal, so I think qqnorm and qqline cannot be applied. Perhaps you can help? Ralf

>>>>> On Tue, 31 Aug 1999 14:57, Werner Stahel <stahel@stat.math.ethz.ch> said: WSt> Here is a suggestion. It seems that qqplots, comparing a sample WSt> to a distribution other than the normal, are not explicitly WSt> available in S or R. I found (in S-plus / Trellis it is, see below) WSt> qqplot(y, rt(300, df = 5)) WSt> as an

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, 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]

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

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, 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)))

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

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 :