The Metalog Distributions

Metalog Software Implementations

Publicly available software implementations of metalog distributions are listed below in order of release date.  These include only software implementations that are known to us.  There are likely others of which we are unaware.

Excel Workbooks

We offer the complete metalog system within free, convenient Excel workbooks programmed by the author of this website. The worksheets in these workbooks are programmed in native Excel, without macros or named ranges, which means that they can be easily and safely copied into other Excel workbooks while retaining their full functionality.  Click here for details.

SIPmath Modeler Tools

SIPMathTM Modeler Tools is a simulation environment in Excel provided by Probability Management as a free Excel add-in. The current version of the Tools offers two implementations. One is the SPT-metalog distributions (e.g. 3-term metalogs parameterized by 10/50/90 quantiles).  Here is a with a tutorial. For the general metalogs (including more terms), we offer a separate tutorial.

SmartOrg's Portfolio Navigator

SmartOrg, which provides a web-based software environment to enable better decision conversations in new product development and portfolio management, includes metalogs in their new release of Portfolio Navigator 7 to aid probability distribution visualization and communication. 

Lumina Decision Systems' Analytica

Lumina Decision Systems, which provides software to help bring clarity to difficult decisions, includes the complete metalog system (as originally published) in the recent release of its flagship product Analytica 5.0. For documentation of Analytica's metalog implementation, click here.

RMetalog Function in R

An RMetalog function is in the advanced stages of development for R. R is an open source programming language and software environment for statistical computing, which is widely used by statisticians and data miners for data analysis and development of statistical software. A beta version of RMetalog, which includes the complete metalog system as originally published, is currently available. Click here for installation and implementation instructions. For questions and feedback, contact Isaac Faber, graduate student in Management Science and Engineering, Stanford University. We anticipate submitting RMetalog to CRAN (Comprehensive R Archive Network) for independent peer review and approval early in 2018.