Dear All, In principle it is a simple question, but not idea about how to tackle it. Suppose you have a distribution depending on two parameters, e.g. beta(a,b). For some reasons, you want to impose that the two parameters of the beta distribution are identical, i.e. you want to fit your data to beta(a,a). For instance x<-rbeta(1000, 0.1, 0.1) require(fitdistrplus) mm<-fitdist(x, "beta", method = "mge") is how you would normally fit a sample, but I do not know how to impose the constrain a=b before the fitting. Any suggestion is appreciated. Cheers Lorenzo
Fitdistrplus and Parameter Constraints
2 messages · Lorenzo Isella, Christophe Dutang
Dear Lorenzo, Please do read the posting guide (https://www.r-project.org/posting-guide.html) : The ?main? R mailing list, for discussion about problems and solutions using R, about the availability of new functionality for R and documentation of R, comparison and compatibility with S-plus, and for the posting of nice examples and benchmarks. For your problem, you could do something like this x <- rbeta(1000, 3, 3) dbeta2 <- function(x, shape, ...) dbeta(x, shape, shape, ...) pbeta2 <- function(q, shape, ...) pbeta(q, shape, shape, ...) library(fitdistrplus) fitdist(x, "beta2", start=list(shape=1/2)) x <- rbeta(1000, .3, .3) fitdist(x, "beta2", start=list(shape=1/2), optim.method="L-BFGS-B", lower=1e-2) Regards, Christophe --------------------------------------- Christophe Dutang LMM, UdM, Le Mans, France web: http://dutangc.free.fr
Le 23 mai 2017 ? 18:22, Lorenzo Isella <lorenzo.isella at gmail.com> a ?crit : Dear All, In principle it is a simple question, but not idea about how to tackle it. Suppose you have a distribution depending on two parameters, e.g. beta(a,b). For some reasons, you want to impose that the two parameters of the beta distribution are identical, i.e. you want to fit your data to beta(a,a). For instance x<-rbeta(1000, 0.1, 0.1) require(fitdistrplus) mm<-fitdist(x, "beta", method = "mge") is how you would normally fit a sample, but I do not know how to impose the constrain a=b before the fitting. Any suggestion is appreciated. Cheers Lorenzo