similar to: Fit Frechet Distribution

Hi everyone, is there a function to fit a frechet distribution? The only thing I found is gev.fit from ismev which fits a generalized extreme value distribution (if shape>1 => Frechet) . Is there a function to only fit a frechet? Thank you Benjamin

hello my data is data2:2743 4678 21427 6194 10286 1505 12811 2161 6853 2625 14542 694 11491 14924 28640 17097 2136 5308 3477 91301 11488 3860 64114 14334 by calculating shape<-(mean(data2))^2/var(data2) scale<-var(data2)/mean(data2) i get the idea what the parameters of the gammadistribution would be. but if i try using the method mle() i get stock and i don't know, how to

hello! i don't want to test my sample data for normality, but exponential- lognormal- or gammadistribution. as i've learnt the anderson-darling-test in R is only for normality and i am not supposed to use the kolmogorov-smirnov test of R for parameter estimates from sample data, is that true? can you help me, how to do this anyway! thank you very much! nadja

my problem actually arised with fitting the data to the weibulldistribution, where it is hard to see, if the proposed parameterestimates make sense. data1:2743;4678;21427;6194;10286;1505;12811;2161;6853;2625;14542;694;11491; ?? ?? ?? ?? ?? 14924;28640;17097;2136;5308;3477;91301;11488;3860;64114;14334 how am I supposed to know what starting values i have to take? i get different

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

Hi, is there any package (or source code snippet) that will evaluate the Frechet distance for curves represented as sets of points? Searching around only threw up references to a Frechet distribution. Thanks, ------------------------------------------------------------------- Rajarshi Guha <rxg218 at psu.edu> <http://jijo.cjb.net> GPG Fingerprint: 0CCA 8EE2 2EEB 25E2 AB04 06F7 1BB9

Dear all I've got the dataset data:2743;4678;21427;6194;10286;1505;12811;2161;6853;2625;14542;694;11491; ?? ?? ?? ?? ?? 14924;28640;17097;2136;5308;3477;91301;11488;3860;64114;14334 I know from other testing that it should be possible to fit the data with the exponentialdistribution. I tried to get parameterestimates for the exponentialdistribution with R, but as the values of the parameter

Dear R helpers I have some data and through some other software, it is understood that I can fit the Frechet Distribution to it. However, I need to fit the distribution using R code only. I have searched many R packages and one R helper has suggested some sites too, but unfortunately parameters couldn't be estimated. Using LMOM package, I know how to estimate the parameters of Generalized

Dear R Helpers This is the R code (which I have slightly changed) I got in VGAM package for estimating the parameters of FRECHET. _________________________________________________________________ y = rfrechet(n <- 100, shape=exp(exp(0))) # (A) fit3 = vglm(y ~ 1, frechet3(ilocation=0), trace=TRUE, maxit=155) # (B) coef(fit3, matrix=TRUE) # (C)

Dear All- I am looking at the bivariate point process model for extreme values as described in Section 8.3.2 of Coles book. I am stuck at a very low level in being unable to reproduce the initial step of transforming the data to unit Frechet margins. In particular, I am unable to reproduce the wave-surge pairs distribution after transformation to Frechet scale (Figure 8.6 of Coles

Good Morning I want to perform a synthetic control method with R. For this purpose, I created the following code: # Re-load packages library(Synth) library(readxl) # Pfadeinstellung Excel-Blatt excel_file_path <- ("C:\\Users\\xxxxx\\Desktop\\DATA_INVESTMENTVOLUMEN_FOR_R_WITHOUT_NA.xlsx") # Load the Excel file INVESTMENTVOLUME <- read_excel(excel_file_path) #

Dear R-Users, I have a question that bothers me in the last few days. It is supposed to be easy but I can't come up with a solution. Are there any functions in R dealing with transforming empirical and parametric distributions? I have two data sets of observed variables that I want to transform to Frechet and Uniform distribution. I would appreciate if someone could inform me about

Hello, I used the following codes to generate bivariate normal dependence structure with unit Frechet margins. Sigma <- matrix(c(1,.5*sqrt(1),.5*sqrt(1),1),2,2) # generate y <- mvrnorm(Nsam, c(0,0), Sigma) # random v <- cbind(pnorm(y[,1],mean = 0, sd = 1), pnorm(y[,2],mean = 0, sd = 1)) z <- cbind(-1/log(v[,1]),-1/log(v[,2])) z1 <- z[,1] z2 <- z[,2] And to

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, If I use the levelplot function of the lattice library, I always see small "squares" in the plot. They indicate the region for which the same color is used. If you have a levelplot of a function which is evaluated at 25x25 equally-spaced points you obtain 26 squares in x and 26 squares in y direction. That does not bother too much (but still bothers somehow...), but if you

Can you please post the following offer to the R listserv members? Chapman & Hall/CRC Press is delighted to offer you a 20% off Discount on our latest and bestselling R books. Please order online at www.crcpress.com. Enter promotion code 783EM to apply discount. Recently Published! Statistical Computing with R Maria L. Rizzo, Bowling Green State University, Bowling Green, OH,

I can''t find network device in domU. Debian domU shows Configuring network interfaces...SIOCSIFADDR: No such device eth0: ERROR while getting interface flags: No such device and Fedora domU shows: eth0: unknown interface: No such device Dom0 is using Fedora with: kernel-xen-guest.i686 2.6.15-1.29_FC5 installed kernel-xen-hypervisor.i686

?kml? is an implementation of k-means for longitudinal data (or trajectories). This algorithm is able to deal with missing value and provides an easy way to re roll the algorithm several times, varying the starting conditions and/or the number of clusters looked for. KmL 1.1.1 addition: - 7 imputations methods for longitudinal data - Calculus of three qualities criterion (Calinski&Harabatz,

?kml? is an implementation of k-means for longitudinal data (or trajectories). This algorithm is able to deal with missing value and provides an easy way to re roll the algorithm several times, varying the starting conditions and/or the number of clusters looked for. KmL 1.1.1 addition: - 7 imputations methods for longitudinal data - Calculus of three qualities criterion (Calinski&Harabatz,

Dear R-"helpers"! May I kindly ask the pure statistics-experts to help me for a purpose which first part is not directly concerned with R. Consider two distribution functions, say f and g. For both, the median is smaller than a half. Now, the multiplicative or additive linkage of both distribution leads to a new distribution function, say h, whereas the median of h is greater than a