similar to: Fw: Fitting GUMBEL Distribution - CDF function and P P Plot

Dear R helpers 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 Plot. My R code is as follows. library(quantreg) library(RODBC) library(MASS) library(actuar) library(lmom) x <-

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

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,

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

Hi, I have a data set which is assumed to follow weibull distr'. How can I find of cdf for this data. For example, for normal data I used (package - lmomco) >cdfnor(15,parnor(lmom.ub(c(df$V1)))) Also, lmomco package does not have functions for finding cdf for some of the distributions like lognormal. Is there any other package, which can handle these distributions?

I saw a Help e-mail related to MLE. Does R have a probability weighted method (PWM) estimator function? I can't seem to find anything on PWM, unless my eyes are playing trick on me. [[alternative HTML version deleted]]

Dear Sir in the following example,is the vector lmom a l-moment ratios vector? What is meant by size = northCascades[,1]? And what are the values in c(0.0104,0.0399,0.0405)? Please help me I am unable to understand these from help manual. Best Regards AMINA data(northCascades) lmom <- c(1, 0.1103, 0.0279, 0.1366) kappaParam <- kappalmom(lmom) heterogeneity(500, 19, size =

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

Hi R-users, I'm trying to repeat the same procedure to 1000 data set. I know this is very easy, but I got stuck finding the right and fastest way in running it. IID50=Riidf[1:50,1:1000] #where IID50 is a dataframe consist of 1000 time series(as column) and 50 time scales (row). #what I tried to do: estIID50=rep(NA,1000) for (i in 1:1000) estIID50[i]=pargev(lmom.ub(IID50[1:50,i])) #warning

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

Hey, I have a set of income data which I'd like to fit to a gamma distribution. How can I estimate the two parameters of the gamma distribution for a vector, e.g. c(2039L, 2088L, 5966L, 2353L, 1966L, 2312L, 3305L, 2013L, 3376L, 3363L, 3567L, 4798L, 2032L, 1699L, 3001L, 2329L, 3944L, 2568L, 1699L, 4545L) I sense this will be a very easy one-liner, but my searching didn't come up with

Hello, I am a new user of R (2.13.1), my operational system is Windows Vista. I have a problem with the attached file SFEVaRHAC.r, calculating the VAR of a Gumbel copula, based on the attached GumHAC_VaR_PL_w250_n1000_s2500.txt 1. I had a Error in file(file, "rt") : cannot open the connection message. I solved it by reading a post in nabble to use setwd(choose.dir()) and

Hi, I found this document, but it concerns S+. If it could interest you'll see: http://faculty.washington.edu/ezivot/book/QuanCopula.pdf Cordially Vito You wrote: Dear R: Is there a function or a reference to simulate Gumbel copulas, please? Thanks in advance! Sincerely, Erin Hodgess mailto: hodgess at gator.uhd.edu R version 2.0.1 windows ===== Diventare costruttori di soluzioni

Hi all! I'm sure this is a stupid question but I can't find an answer. How can I fit the Gumbel distribution to my data using The Method of Moments in R? Thank you for helping me, Tonja

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]]

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) =

Dear ALL I have a list of data below 0.80010 0.72299 0.69893 0.99597 0.89200 0.69312 0.73613 1.13559 0.85009 0.85804 0.73324 1.04826 0.84002 1.76330 0.71980 0.89416 0.89450 0.98670 0.83571 0.73833 0.66549 0.93641 0.80418 0.95285 0.76876 0.82588 1.09394 1.00195 1.14976 0.80008 1.11947 1.09484 0.81494 0.68696 0.82364 0.84390 0.71402 0.80293 1.02873 all of them are ninty. Nowaday, i try to find a

Dear R forum >From the given data, I have estimated the parameters of Wakeby distribution using lmomco package as library(lmomco) (amounts <- read.csv("input_S.csv")$amount) # ___________________________________________________________ # Wakeby distribution - Parameter estimation N                      = length(amounts) lmr                    = lmom.ub(amounts)

Hi List! I?m using regsimq() from the ?lmomRFA?-package to calculate error bounds for diverse distributions. For example: regsimq(gumfit$qfunc, nrec = lmom.data$n, f = lcdfgum, boundprob = c(0.025, 0.975)) Several times I got this error massage: Fehler in quantile.default(ou, probs = boundprob, type = 6) : missing values and NaN's not allowed if 'na.rm' is FALSE So my question

Hi! Unfortunately the version loaded on the office server is 2.6.0 (for some undisclosed so called policy decision by my adamant IT dept. who are not willing to upgrade), I need to use YieldCurve package compatible with this version. On my standalone machine I have R 2.9 loaded and hence I have no problem in using the YieldCurve package. (a) Kindly guide how do I download the version of