similar to: "actuar" package query

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

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

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

=== 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

Hola, Estoy intentando esta convolución con una discretizada Gamma con Binomial negativa pero me da el siguiente error. Alguien sabe como puedo hacer funcional este algoritmo con estos parámetros? > fx<-discretize(pgamma(x,shape=2.4149,scale=5742.2), + method="rounding",from=0, to =100, step=0.5) > Fs <- aggregateDist("recursive", model.freq = "negative

We obtained some disturbing results from convolve() (inaccuracies and negative probabilities). We'll try to make the context clear in as few lines as possible... Our function panjer() (code below) basically computes recursively the probability mass function of a compound Poisson distribution. When the Poisson parameter lambda is very large, the starting value of the recursive scheme ---

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

Dear Charles, Please, when you have questions about fitdistrplus, contact directly the authors of the package and not R-help. When fitting non ? standard ? distributions with fitdistrplus, you should define by yourself the density and the cumulative distribution functions, or load a package which define them. See FAQ for a general example :

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

Dear all, I have the cdf of the following power fuction distribution: F(y)=(y/350)^a               ,0<y<350, where " a " is some parameter with range a>0. I want to use it as the argument of the discretize function of the actuar package. So I think I need to define this function to R so that if I entered a=1, I get the following F(y)=(y/350) and if I entered a=4.5, I get the

Hi , I am trying to get some estimator based on lognormal distribution when we have left,interval, and right censored data. Since, there is now avalible pakage in R can help me in this, I had to write my own code using Newton Raphson method which requires first and second derivative of log likelihood but my problem after runing the code is the estimators were too high. with this email ,I provide

Sir, I want to draw random from any multivariate disrtibution. Is there any function in R to do this? Regards, Suman Dhara [[alternative HTML version deleted]]

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, ?

Dear Carlos, Duncan and everyone You may have already sorted the matter by now, but since I have not seen anything posted since Duncan's reply, here I go. I apologize in advance for the spam, if it turns out I've missed some post. I think the test and the implementation of the truncgof package are just fine. I've done Carlos' experiment (repeatedly generating samples and testing

In theory, dlnorm(x, ...) == dnorm(log(x), ...)/x, x>0. Unfortunately, when sd=0, dlnorm and plnorm return NaN, while dnorm returns (if(x != mean)0 else Inf) and pnorm returns (if(x<mean)0 else 1). [A numerical optimization, maxLik{maxLik}, reported the NaNs for me.] help('dlnorm') says, "dlnorm is calculated from the definition (in ?Details?). [pqr]lnorm are based on the