similar to: Fitting an Inverse Gamma Distribution

Hello, I've been attempting to fit the data below with an inverse gamma distribution. The reason for this is outside proprietary software (@Risk) kicked back a Pearson5 (inverse gamma) as the best fitting distribution with a Chi-Sqr goodness-of-fit roughly 40% better than with a log-normal fit. Looking up "Inverse gamma" on this forum led me the following post:

Dear all, I am new in R and would like to ask for someone's help in understanding where I go wrong with the following code: rm(list=ls()) # Required packages library(MCMCpack) # Simulated data set.seed(1) data = rinvgamma(n=250, shape = 5, scale = 2) + 2 hist(data) # log-likelihood ll = function(par){ if(par[1]>0 & par[2]>0 & par[3]<min(data)) return(

Hi Everybody, Thanks in advance for your help. This is my first time using the foreach statement and I cant get it to work properly so here is what i have test<-function(){ repeat { cand2[l-1]<-rinvgamma(1,phi,lambda[l-1]) q2<-dinvgamma(cand2[l-1],phi,lambda[l-1]) p2<-cand2[l-1]^-1.5*exp(-y[l]^2/(2*cand2[l-1]))*exp(-((log(cand2[l-1])-mu_t_cand[l-1])^2)/2*sigmasq)

Hello. I am not certain even how to search the archives for this particular question, so if there is an obvious answer, please smack me with a large halibut and send me to the URLs. I have been experimenting with fitting curves by using both maximum likelihood and maximum spacing estimation techniques. Originally, I have been writing distribution-specific functions in 'R' which work

Hi there, I had a serious problem here . Consider the following Bayesian model(discretized variance gamma): #Likelihood J[i]<-lambda*G[i]+sigma*sqrt(G[i])*rnorm(0,1) G[i]<-rgamma(1/nu,1/nu) #Prior: nu<-rinvgamma(m,M) # Parameters lambda=-.04 ; sigam=.38; nu=6.48; m=10,M=10 ; T=5000 (length of data) An author claimed that he got posterior distribution

Hello: Could anyone point me to a nice example where someone has created methods for "[" on a user defined Class? I looked at the package Matrix but that was a little daunting. I'm looking for someone a little more introductory. I've tried to search the help section and the web but its difficult since "[" isn't searchable. Thanks in advance! Greg [[alternative

=== actuar: An R Package for Actuarial Science === We are pleased to announce the immediate availability of version 1.0-0 of actuar. This release follows publication of our papers in JSS (*) and R News (**). From the NEWS file: Version 1.0-0 ============= NEW FEATURES o Improved support for regression credibility models. There is now an option to make the computations with the

=== actuar: An R Package for Actuarial Science === We are pleased to announce the immediate availability of version 1.0-0 of actuar. This release follows publication of our papers in JSS (*) and R News (**). From the NEWS file: Version 1.0-0 ============= NEW FEATURES o Improved support for regression credibility models. There is now an option to make the computations with the

Dear useRs, A new version of actuar is available since last Friday. This is mainly a bugfix release. From the NEWS file: Version 1.0-2 ============= USER-VISIBLE CHANGES o m<foo>() and lev<foo>() now return Inf instead of NaN for infinite moments. (Thanks to David Humke for the idea.) BUG FIXES o Non-ascii characters in one R source file prevented compilation of the package in

Dear useRs, A new version of actuar is available since last Friday. This is mainly a bugfix release. From the NEWS file: Version 1.0-2 ============= USER-VISIBLE CHANGES o m<foo>() and lev<foo>() now return Inf instead of NaN for infinite moments. (Thanks to David Humke for the idea.) BUG FIXES o Non-ascii characters in one R source file prevented compilation of the package in

I run the following: library(actuar) x <- seq(0, 22, 0.5) fl <- discretize(plnorm(x, 2.1), from = 0, to = 22, step = 0.5, method ="lower") Fs <- aggregateDist("recursive", model.freq = "poisson",model.sev = fl, lambda = 10, x.scale = 0.5) Warning message: In panjer(fx = model.sev, dist = dist, p0 = p0, x.scale = x.scale, : maximum number of recursions

Dear useRs, I'm happy to announce a substantial update of package actuar that bumps the version number to 2.0-0. This release focuses on additional support for continuous and discrete distributions, new functions to simulate data from compound models and mixtures, and revised and improved documentation. A slightly shortened version of the NEWS file follows: NEW FEATURES ? Support for the

Dear useRs, I'm happy to announce a substantial update of package actuar that bumps the version number to 2.0-0. This release focuses on additional support for continuous and discrete distributions, new functions to simulate data from compound models and mixtures, and revised and improved documentation. A slightly shortened version of the NEWS file follows: NEW FEATURES ? Support for the

Hola a tod@s, Hace poco en la lista se discutieron algunas aproximaciones para determinar la distribución de probabilidad que potencialmente podrían haber generado los datos (ver [1]) y una de ellas fué el AIC. Haciendo uso del programa enviado por Pablo Verde (ver [1]), estos son los resultados para mis datos: weibull , AIC = 69839.44 exponential , AIC = 79488.77 gaussian , AIC = 69413.03

UseRs, Version 0.9-4 of actuar should be making its way to CRAN mirrors. The main highlights of this new version are speed enhancements for a few functions, support for phase-type distributions and functions for ruin theory. The relevant section of the NEWS file follows Version 0.9-4 ============= Maintenance and new features release. NEW FEATURES -- LOSS DISTRIBUTIONS o Functions

UseRs, Version 0.9-4 of actuar should be making its way to CRAN mirrors. The main highlights of this new version are speed enhancements for a few functions, support for phase-type distributions and functions for ruin theory. The relevant section of the NEWS file follows Version 0.9-4 ============= Maintenance and new features release. NEW FEATURES -- LOSS DISTRIBUTIONS o Functions

Der r helpers, I have a following set of data. Though some other software, I know it follows 3 parameter Gamma distrinution. I need to write a R code for estimating the parameters of 3 Parameter Gamma distribution. c(0,0,18561.9,0,0,0,34400,0,0,0,0,2190,0,0,0,0,60000,0,0,0, ? 19583,0,0,0,109872.87,0,0,0,0,0,0,1244,0,0,25150,0,500,0,0,0, ?

UseRs, actuar is a package for Actuarial Science. A rather preliminary version (0.1-3) of the package has been available on CRAN since February 2006. We now announce the immediate availability of version 0.9-2 sporting a large number of new features. Non actuaries behold! There can be some features of interest for you, especially those related to new probability distribution and to the

UseRs, actuar is a package for Actuarial Science. A rather preliminary version (0.1-3) of the package has been available on CRAN since February 2006. We now announce the immediate availability of version 0.9-2 sporting a large number of new features. Non actuaries behold! There can be some features of interest for you, especially those related to new probability distribution and to the

Dear developeRs, Compilation of the latest version (0.9-5) of my actuar package fails with r-release MacOS_X ix86 on CRAN; see http://www.R-project.org/nosvn/R.check/r-release-macosx-ix86/actuar-00check.html All errors come from accented letters in comments in latin-1 encoded files (except hierarc.R which is in UTF-8, my bad). Encoding is declared as latin-1 in DESCRIPTION. The package