Claude Shannon’s information theory says you can’t store 100 million numbers in 88 bytes.

True, but Tom Keelin’s Metalog distribution driven by Doug Hubbard’s HDR pseudo-random number generator, can create identical streams of up to 100 million random variates on any platform. Like Taylor series, Metalogs can take any number of terms (see Wikipedia). But for practical purposes 18 parameters will model virtually any continuous distribution you will face. In its standard configuration, the HDR generator takes up to four initialization seeds, which provides great flexibility when sharing SIPMath™ 3.0 Libraries with others. The version of the HDR built into our tools, which has been limited in numerical accuracy to support Excel, can generate 100 million random numbers before the rubber band breaks (well actually the results on dieharder test deteriorate). So that’s a total of 22 input parameters (88 bytes) to generate nearly any distribution. The open SIPmath standard wraps these 22 parameters in JSON objects containing metadata, that can be used in Excel, Python, R, or virtually any other computer platform.

The first commercial package to read and write the SIPmath 3.0 was Frontline Systems Analytic Solver. This powerful Excel add-in, performs both simulation and optimization, including stochastic optimization. Now our new interface to Tom Keelin’s elegant Excel Metalog templates can let you create 3.0 JSON libraries, or paste Metalog simulation formulas directly into Excel for use with ChanceCalc, The SIPmath Tools, @RISK, or Crystal Ball.