similar to: Calculation of Central Moments

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")

I have an external data (.txt) for annual peak flood. The first column is the year, second column is the observation date, and the last is the observed discharge. My task is to calculate the mean, skewness and kurtosis of the said data. I was advised to use read.table() to read the entire data. Please help me on how to perform the required computation. I am obviously a new user of this statistical

I'm looking for a function that lists a few summary stats for a column (or row) of data. I'm aware of summary(x), but that does not give me what I'm looking for. I'm actually looking for something that is very similar to the descriptive statistics tool in excel; i.e. Mean, Std. Error, Std. Deviation, Kurtosis. I'm positive that I came across a function that did this (possibly

Dear R Helpers Which package is available for estimatine the parameters of three parameter FRECHET distribution. Also, how to generate the random numbers for Frechet using these three estimated parameters. Thanking in advance Maithili

Dear R helpers   I have two series A and B as given below -   A <- c(2, 2, 1, 3, 7, 3, 3, 1, 14, 7, 31) B <- c(0.0728,0.9538,4.0140,0.0020,2.5593,0.1620,2.513,0.3798, .0033,0.2282, 0.1614)   I need to calculate the total in dataset B corresponding to the numbers in dataset A i.e. for no 1 in A, I need the total as 4.0140+0.3798 (as 1 is repeated twice) for no 2, I need the total as

Dera R Helpers, I am re-posting my query. Please guide me. Maithili --- On Fri, 3/13/09, Maithili Shiva <maithili_shiva at yahoo.com> wrote: I am trying to fit the Gumbel distribution to a data. I am using lmom package. I am getting problem in Cumulative Distribution Function of Gumbel distribution as I am getting it as a series of 0's and 1's thereby affecting the P P

Dear R helpers   Suppose   M <- c(1:10)      #  length(M) = 10 N <- c(25:50)     #  length(N) = 26    I wish to have an outut file giving M and N. So I have tried   write.csv(data.frame(M, N), 'output.csv', row.names = FALSE)   but I get the following error message   Error in data.frame(M, N) :   arguments imply differing number of rows: 10, 26   How do I modify my write.csv

Hi R helpers, I have two matrices A and B of the order (4 * 5) and (5 * 3) respectively. How to multiply these two matrices to obtain resultant matrix of the order (4 * 3). Thanks in advance With regards Maithili

Hi! I am working on scorecard model and I have arrived at the regression equation. I have used logistic regression using R. My question is how do I validate this model? I do have hold out sample of 5000 customers. Please guide me. Problem is I had never used Logistic regression earlier neither I am used to credit scoring models. Thanks in advance Maithili

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

Dear Sirs, ? At the outset I sincerely apologize for reproducing my query to you. I also thank all of you for the solution you had provided. It has worked on the actual data I am working with. ? However, there is this peculiar problem which I had realized only after I had obtained my results. ? e.g. in the example I had attached ? A?<-?c(2, 2, 1, 3, 7, 3, 3, 1,?14, 7, 31) B?<-

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

Dear R helpers Suppose I have a portfolio of securities with exposure to Equity, Bonds and Forex (say $ 1000000 each). Is there any fucntion in R that will help me calculate Value at Risk (VaR) using Monte carlo Simulation , Historic simulation and Variance - Covariance Simulation. With regards Maithili

Dear R Helpers, Is there any literaure available (including R code) on Fast Fourier Transform being used in CreditRisk+? I need to learn how to apply the Fast Fourier Transform. I agree I am too vaue in my question and sincerely apologize for the same, but I am not able to understand as to where do I start for this particular assignment. I tried to search google for CRAN and Fast Fourier

Dear R helpers,   I understand that this is absolutely unprofessional on my part and this group doesn't entertain such things. I have been associted with this group since last 1 and half years and have been immensely benefited by the noble service rendred by many R helpers.   So I take this opportunity to thank all of you and wish you all   "MERRY CHRISTMAS".   I sincerely apologize

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 R-Users, The following questions are not R-technical, but more of general statistical nature. 1. NORMALITY I built a normal linear regression model and now I want to check for the residual normality assumption. If I check the distribution graphically and look at the descriptive characteristics (skewness and kurtosis are below 1), I would confirm that the residuals are normally

Hi R helpers, Is there any function in R, which generates random numbers in case of (1) Generalized Extreme Value distribution and (2) Generalized PAreto distribution for the respective given set of parameters? Regards Maithili

Dear R helpers,   I have a data of 2102 observations (consisting of 0's also), to which I am trying to fit Normal distribution using "lmom" pacakage. If I use Excel, its easy to estimate the parameters of Normal distribution as simple mean and standard devaition. The results I get if I use teh excel are as   Parameters of Normal distribution :-   Mean = 22986.44 and standard