Visual interactive fitting of bounded Johnson distributions

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Abstract
We present a visual, interactive method for specifying a bounded Johnson (SB) probability distribution when little or no data are available for formally identifying and fitting an input process. Using subjective information, the modeler provides values for familiar characteristics of an envisioned target distribution. These numerical characteristics are transformed into parameter values for the probability density function. The parameters can then be indirectly manipulated, either by revising the desired numerical values of the function's specifiable characteristics or by directly altering the shape of the displayed curve. Interaction with a visual display of the fitted density permits the modeler to conveniently obtain a more realistic representation of an in put process than was previously possible. The techniques involved have been packaged into a public-domain microcomputer-based software system called VISIFIT.

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