similar to: KS and AD test for Generalized PAreto and Generalized Extreme value

Up to now, I have recognized problems with "gpd(..)", the function from the package "evir" I think that all these functions that estimate the parameters xi, beta for the GPD by given threshold mu use the function "optim(..)" ( gpd, fitgpd, ...) "Error" example: data1 <- rgpd(1000, xi= -1.5, mu=1000, beta=100) so the created poinnts take place in about

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,

Hello, I am using the lmomco package (lmom.ub and pargev) to compute the GEV parameters (location, scale, and shape), which are used to estimate return values. I was wondering how/if I can calculate upper and lower confidence (CI_u, CI_l) intervals for each return frequency using the GEV parameters to fill-in the table below? Xi (location) = 35.396 Alpha (scale) = 1.726 Kappa (shape) =

Hi guys, I'm trying to use lmomco package. first I did the manual calculation on what is the estimates scale and location parameter given L-CV=0.2, L1=1000 L-moments and k (shape parameter) =- 0.1. so what i get is: location: 821.0445 scale: 260.7590 shape: -0.1000 #I assign this as GEV vectors using vec2par GEVpara2<-vec2par(c( 821.0445 , 260.7590 ,-0.1),'gev') #then I

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

Hello all, I would like to plot the emperical CDF, normal CDF and pareto CDF in the same graph and I amusing the following codes. "z" is a vector and I just need the part when z between 1.6 and 3. plot(ecdf(z), do.points=FALSE, verticals=TRUE, xlim=c(1.6,3),ylim=c(1-sum(z>1.6)/length(z), 1)) x <- seq(1.6, 3, 0.1) lines(x,pgpd(x, 1.544,0.4373,-0.2398), col="red") y

Hi, I'm a second year Master's student in Applied Statistics. I am doing a project using average weekly U.S. regular gasoline prices (in cents, per gallon) from an Excel file (from the years 1990- May 2010). I want to find the probability that the average weekly U.S. regular gasoline prices (in the long term) goes over 400 cents a gallon (or $4.00 a gallon). I am using the

Dear R helpers, How do you estimate the (Location, Scale, Shape) parameters of Generalized Extreme Value distribution using R? I have tried VGAM but just not able to write the R script. Please advise. With regards Maithili

I would like to fit a Pareto Distribution and I am using the following codes. I thought the fitted (fit1) should be the fitted value for the data, is it correct? As the result of the "fitted" turns out to be a single value for all. fit=vglm(ycf1 ~ 1, pareto1(location=alpha), trace=TRUE, crit="c") fitted(fit) The result is fitted(fit) [,1] [1,] 0.07752694

Hi, I have been having difficulties in finding packages/ codes that simplify plotting of a GEV fitted to dataset (by L-moments) that would print out graph comprising dataset versus gumbel reduced variate n return period at the same. Anyone can help me on this? Thanks. [[alternative HTML version deleted]]

Hi, I'm fitting a generalized Pareto distribution to POT exceedances of a data set. The practical stuff works ok, but I have a question regarding theory. Is there an equation relating parameters of a gpd tail to its (first) moments? According to theory for certain parameters either the first moment does not exist or the distribution has an upper bound, but I haven't found the

Dear List, As someone who is in the process of trying to migrate from Excel, I'd appreciate any help on this question: I have a data set and want to fit, say, three distributions to it. I would like to create a plot that shows my data points against all three fitted curves (estimated d.f.). Basically, I lookint to creat a plot that looks like the one presented in the attached paper (Figure

Hi all, I'd like to export the results of GPD or GEV analysis generated with the Extremes Toolbox for plotting in Grapher or Excel (for manipulation by our publications group). Is it possible to access the data used to generate the plots in extRemes, or do I need to code the analysis from scratch and write to file? Thanks, Ben Stay connected to the people that matter most with a

Hi, I'd like to export the results of GPD or GEV analysis generated with the Extremes Toolbox for plotting in Grapher or Excel (for manipulation by our publications group). Is it possible to access the data used to generate the plots in extRemes, or do I need to code the analysis from scratch and write to a file? Stay connected to the people that matter most with a smarter inbox.

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

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

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 useRs, upon request, the VGAM package (currently version 0.7-1) has been officially released on CRAN (the package has been at my website http://www.stat.auckland.ac.nz/~yee/VGAM for a number of years now). VGAM implements a general framework for several classes of regression models using iteratively reweighted least squares (IRLS). The key ideas are Fisher scoring, generalized linear and

Hi, I am trying the following: library(ismev) library(evd) fit <- gev.fit(x,show=FALSE) ks.test(x,pgev,fit$mle[1],fit$mle[2],fit$mle[3]) but I am getting: Warning message: cannot compute correct p-values with ties in: ks.test(x, pgev, fit$mle[1], fit$mle[2], fit$mle[3]) where x is: [1] 239 38 1 43 22 1 5 9 15 6 1 9 156 25 3 100 6 [18] 5 100

Hi: I am going through some of the xtable examples and I can't make the one below work. I need to create a longtable on the fly keeping the column headers for all the pages and I thought this example could give some ideas on how to do it. I am using Sweave and xtable to create my tables and graphics. I wonder if someone could tell me what's wrong. Thanks ## Not run: \begin{small}