Dear All, Apologies for not providing a reproducible example, but if I could, then I would be able to answer myself my question. Essentially, I am trying to fit a very complicated custom probability distribution to some data. Fitdistrplus does in principle everything which I need, but if require me to specify not only the density function d, but also the cumulative p and and inverse cumulative function q (see for instance http://www.stat.umn.edu/geyer/old/5101/rlook.html to understand what these quantities are in the case of a normal distribution). The analytical calculation of p and q is a big task in my case, so my question is if there is a workaround for this, i.e. a way to fit the unknown parameters of my probability distribution without specifying (at least analytically) p and q, but only the density d. Many thanks Lorenzo [[alternative HTML version deleted]]

Why not define your own functions based on d? e.g. myCumDist <- function(x) { integrate(d, lower=-Inf, upper=x)$value } myQuantile <- function(x) { uniroot(f=function(y) { h(y) - x }, interval=c(-5,5)) } # limits -5,5 should be replaced by your own which might require some fiddling e.g. d <- function(x) { exp(-x^2/2)/(sqrt(2*pi)) } # just an example for you to test with; use your own density d(x) in your case Then define myCumDist, myQuantile as above and compare with pnorm, qnorm. HTH, Eric On Tue, Nov 7, 2017 at 4:22 PM, Lorenzo Isella <lorenzo.isella at gmail.com> wrote:> Dear All, > Apologies for not providing a reproducible example, but if I could, then I > would be able to answer myself my question. > Essentially, I am trying to fit a very complicated custom probability > distribution to some data. > Fitdistrplus does in principle everything which I need, but if require me > to specify not only the density function d, but also the cumulative p and > and inverse cumulative function q (see for instance > > http://www.stat.umn.edu/geyer/old/5101/rlook.html > > to understand what these quantities are in the case of a normal > distribution). > > The analytical calculation of p and q is a big task in my case, so my > question is if there is a workaround for this, i.e. a way to fit the > unknown parameters of my probability distribution without specifying (at > least analytically) p and q, but only the density d. > Many thanks > > Lorenzo > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/ > posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >[[alternative HTML version deleted]]