Distribution Fitting and Evaluation
The Burr distribution
Burr coefficients after power-law transformation
Pareto scale determination à la Clauset
Pareto scale determination à la Clauset
Parametrise two-/three- composite distribution
Combined distributions MLE
Combined distributions
Combined coefficients of power-law transformed combined distribution
Composite MLE
The two- or three-composite distribution
Composite coefficients after power-law transformation
Double-Pareto Lognormal MLE
The Double-Pareto Lognormal distribution
Double-Pareto Lognormal coefficients of power-law transformed Double-P...
The empirical distribution
The Exponential distribution
Fréchet MLE
The Fréchet distribution
Fréchet coefficients after power-law transformation
The Gamma distribution
Inverse Pareto MLE
The Inverse Pareto distribution
Inverse Pareto coefficients after power-law transformation
Left-Pareto Lognormal MLE
The Left-Pareto Lognormal distribution
Left-Pareto Lognormal coefficients of power-law transformed Left-Paret...
Vuong's closeness test
The Lognormal distribution
Log Normal coefficients of power-law transformed log normal
Normalized Absolute Deviation
Pareto MLE
The Pareto distribution
Pareto coefficients after power-law transformation
Right-Pareto Lognormal MLE
The Right-Pareto Lognormal distribution
Right-Pareto Lognormal coefficients of power-law transformed Right-Par...
Truncated distribution
The Weibull distribution
Weibull coefficients of power-law transformed Weibull
A library of density, distribution function, quantile function, (bounded) raw moments and random generation for a collection of distributions relevant for the firm size literature. Additionally, the package contains tools to fit these distributions using maximum likelihood and evaluate these distributions based on (i) log-likelihood ratio and (ii) deviations between the empirical and parametrically implied moments of the distributions. We add flexibility by allowing the considered distributions to be combined into piecewise composite or finite mixture distributions, as well as to be used when truncated. See Dewitte (2020) <https://hdl.handle.net/1854/LU-8644700> for a description and application of methods available in this package.