knitr::opts_chunk$set(echo = TRUE)
The implemented distributions are found in univariateML_models
.
library("univariateML") univariateML_models
This package follows a naming convention for the ml***
functions. To access the
documentation of the distribution associated with an ml***
function, write package::d***
.
For instance, to find the documentation for the log-gamma distribution write
?actuar::dlgamma
Additional information about the models can found in univariateML_metadata
.
univariateML_metadata[["mllgser"]]
From the metadata you can read that
mllgser
estimates the parameters N
and s
.extraDistr::dlgser
.Some estimation procedures will fail under certain circumstances. Sometimes due to numerical problems, but also because the maximum likelihood estimator fails to exist. Here is a possibly non-exhaustive list of known problematic distributions.
extraDistr
.b
parameter tends towards 0, the Gompertz tends towards an exponential. A failing estimation indicates the exponential has a better fit.shape1*shape2
converges to a constant while shape2
tends to infinity. Any scripts or data that you put into this service are public.
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