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The metalog distribution is a generalization of the logistic distribution, where the term "metalog" is short for "metalogistic".Starting with the logistic quantile function, = = + (), Keelin substituted power series expansions in cumulative probability = for the and the parameters, which control location and scale, respectively.
The metalog distribution is generalization of the logistic distribution, in which power series expansions in terms of are substituted for logistic parameters and . The resulting metalog quantile function is highly shape flexible, has a simple closed form, and can be fit to data with linear least squares.
The map-Airy distribution; The metalog distribution, which is highly shape-flexible, has simple closed forms, and can be parameterized with data using linear least squares. The normal distribution, also called the Gaussian or the bell curve.
The unbounded metalog distribution, which is a power series expansion of the and parameters of the logistic quantile function. The semi-bounded and bounded metalog distributions, which are the log and logit transforms, respectively, of the unbounded metalog distribution.
For other families of distributions that have also been called generalized logistic distributions, see the shifted log-logistic distribution, which is a generalization of the log-logistic distribution; and the metalog ("meta-logistic") distribution, which is highly shape-and-bounds flexible and can be fit to data with linear least squares.
Quantile parameterized distributions (QPDs) are convenient for inverse transform sampling in this context. In particular, the Metalog distribution is a flexible continuous probability distribution that has simple closed form equations, can be directly parameterized by data, using only a handful of parameters. [6]
Another generalized log-logistic distribution is the log-transform of the metalog distribution, in which power series expansions in terms of are substituted for logistic distribution parameters and . The resulting log-metalog distribution is highly shape flexible, has simple closed form PDF and quantile function , can be fit to data with linear ...
Metalog distribution; Method of moments (statistics) ... Multivariate distribution – see Joint probability distribution; Multivariate kernel density estimation;