search for: momentous

I''m on a Win2K server environnement running ruby 1.8.5 and mongrel I''ve followed the tutorial and everything went fine until I start the service... Here is the output I''m getting : C:\ruby\bin??>mongrel_rails service::start -N inventaire One moment, start pending One moment, stopped One moment, stopped One moment, stopped One moment, stopped One moment, stopped

Dear Experts, If I have a vector of numbers x. (1) How can I write R code to compute the moments around zero of order one to four? (2) How can I write R code to compute the moments around the mean of order one to four? Thank you very much! -- View this message in context: http://r.789695.n4.nabble.com/Writing-R-code-for-moments-tp2967946p2967946.html Sent from the R help mailing list archive

Hi. I was trying to calculate 2. order moment for a loggamma sample. Also, I checked it with the function mlgamma from the package actuar, which calculates moments based on loggamma parameters. Se below - I get big deviations. Numerical integration suggests that mlgamma gets it right. What fails in my attempt to use SLLN to estimate the 2. order moments? Code: sum(rlgamma(10^6,25,2.6)^2)/10^6

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")

Dear listusers, I don't know whether my problem is statistical or computational, but I hope I could recieve some help in either case. I'm currently working on a MC-simulation in which I would like to control the skewness of a heteroscedastic dependent variable defined as: y=d*z+sqrt(.5+.5*x^2)*e (eq.1) where d is a parameter and, z, x, and e are gamma r.vs. The variables x

hello all, my first post so bear with me i have been lossing hair over getting black and white 2 to run on wine i finally got it down to this h4x0r@Mainframe:~/.wine/drive_c/Program Files/Lionhead Studios/Black & White 2$ wine white.exe fixme:system:SystemParametersInfoW Unimplemented action: 112 (SPI_GETMOUSESPEED) fixme:powermgnt:GetSystemPowerStatus (): stub, harmless. wine: Call from

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

Can anyone show me how to add a log Pearson type III plot using the evdistq() command to an extreme value plot using the lmom package? Attached sample code below... Thanks in advance, Dave library(lmom) # annual maximum daily streamflows Mackenzie River mackenzieRiver = c(26600, 30300, 34000, 32000, 29200, 28300, 28600, 26400, 28300, 28800, 29000, 22100, 32900, 31800, 21600, 32100, 27000,

When going through my earlier post I find a mistake in the example that I provided. The correct version is provided below. I also start to suspect that my problem is that although the cumulant of a sum of independent variable is the sum of the cumulants, the moments of a sum is not the sum of the moments. But that might not be the only flaw in my application. Regards, Karl-Oskar #An

moments::anscombe.test(x) does give errors when x has too few values or if all the values in x are the same > moments::anscombe.test(c(1,2,6)) Error in if (pval > 1) pval <- 2 - pval : missing value where TRUE/FALSE needed > moments::anscombe.test(c(2,2,2,2,2,2,2,2)) Error in if (pval > 1) pval <- 2 - pval : missing value where TRUE/FALSE needed You can use tryCatch() to

Hi all, While running the anscombe.test in R, I'm getting an error of *Error in if (pval > 1) pval <- 2 - pval : missing value where TRUE/FALSE needed* for a few time series columns whereas for most of the series the function is working fine. I have checked for those specific columns for missing values. However, there is no NA/NAN value in the dataset. I have also run kurtosis for

Hi Bill, Thanks for prompt reply and letting me know a way around it. I have more than 1200 observations and not all the values are the same. However, my data points are quite similar, for example, 0.079275, 0.078867, 0.070716 in millions and etc. I have run the data without converting it to millions and I still get the same error message. As I have kurtosis value, it should be fine for the

Dear R helpers If for a given data, I need to calculate Mean, Standard Deviation, Mode, Median, Skewness, Kurtosis, is there any package in R, which will calculate these moments? Individually I can calculate these, but if there is any function which will calculate these at a stretch, please let me know. Maithili The INTERNET now has a personality. YOURS! See your Yahoo! Homepage.

How to adapt this piece of code but for: - gamma distribution - 3 parameter log normal More specifically, where can I find the specification of the parameter (lmom) for pelgam() and pelln3()? Lmom package info just gives: pelgam(lmom), lelln3(lmom), where lmom is a numeric vector containing the L-moments of the distribution or of a data sample. # Draw an L-moment ratio diagram and add a line for

Another bad case is > moments::anscombe.test(rep(c(1,1.1),length=35)) Error in if (pval > 1) pval <- 2 - pval : missing value where TRUE/FALSE needed I haven't checked the formulas carefully, but I suspect the problem is from taking the cube root of a negative number in z <- (1 - 2/(9 * a) - ((1 - 2/a)/(1 + xx * sqrt(2/(a - 4))))^(1/3))/sqrt(2/(9 * a)) In R, the

Dear R-list, I apologize for my many emails but I think I know how to desctribe my problem differently and more clearly. My question is how to compare linear models with intercept and those without intercept using maximizing adjusted R^2 strategy. Now I do it like the following: > library(leaps) > n=20 > x=matrix(rnorm(n*3),ncol=3) > b=c(1,2,0) > intercept=1 >

Respected Sir I have to select a probability distribution using L-moment Ratio Diagram. I am not understanding how to plot sample TAU3 and TUA4 on L-moment Ratio Diagram. Please Guide me Best Regards -- AMINA SHAHZADI Department of Statistics GC University Lahore, Pakistan. Email: amnakhan493@gmail.com amna_989@hotmail.com amna_989@yahoo.com [[alternative HTML version deleted]]

Hi everyone, In the package POT, there is a function that computes the L-moments of a given sample (samlmu). However, to compute those L-moments, one needs to obtain the total number of combinations between two numbers, which, by the way, requires the use of a factorial. See, for example, Hosking (1990 , p. 113). How does the function "samlmu" in the package POT avoids overflows? I

On Fri, Feb 18, 2011 at 1:45 PM, Scot P. Floess <sfloess at nc.rr.com> wrote: > > I'd expect better behavior and conduct from someone who holds such a > title... <request for a learning moment> Since beauty is in the eye of the beholder(s), please select my most egregious post(s) and let me know said post(s) so that I have the opportunity to better modify my behavior with

Hello, I estimated a model using SEM package in R, which was fit to a raw moment matrix, and includes an intercept term. The only goodness of fit statistics that are output are Model Chisquare, AIC, AICc, BIC, CAIC, and normalized residuals. How can I get the other goodness of fit statistics, like adjusted goodness of fit, RMSEA, and R-squared? And how can I get the final value of the