Among the most flexible and easy-to-use continuous probability distributions, the metalogs have an increasingly wide range of practical uses:
Allow empirical data to "speak for itself" with highly-flexible continuous-distribution representations.
Get instant continuous-distribution representations for a wide range of 10/50/90 quantile assessments -- ideal for decision analysis applications.
Select among unbounded, semi-bounded, or bounded distributions according to your application
Skip time-consuming parameter estimation: the input CDF (cumulative distribution function) data are themselves the parameters.
Use metalogs as convenient input distributions for Monte Carlo simulation: just generate a uniform random number (e.g. with the Excel RAND() function), and compute your sample using a simple closed-form algebraic equation.
Conveniently represent Monte Carlo simulation outputs as smooth, continuous probability distributions -- obviating the need for histograms or other artificially-lumpy output displays.
Generally, metalogs are useful in a wide range of situations in which CDF data are known, and a simple, flexible, easy-to-use continuous probability distribution is needed to represent that data.
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