Squiggle Language

Squiggle is a minimalist programming language for probabilistic estimation. It's meant for intuitively-driven quantitative estimation instead of data analysis or data-driven statistical techniques.

What Squiggle Is

• A simple programming language for doing math with probability distributions.
• An embeddable language that can be used in Javascript applications.
• A tool to encode functions as forecasts that can be embedded in other applications.

What Squiggle Is Not

• A complete replacement for enterprise Risk Analysis tools. (See Crystal Ball, @Risk, Lumina Analytica)
• A probabilistic programming language. Squiggle does not support Bayesian inference.
• A tool for substantial data analysis. (See programming languages like Python or Julia)
• A programming language for anything other than estimation.
• A visually-driven tool. (See Guesstimate and Causal)

Strengths

• Simple and readable syntax, especially for dealing with probabilistic math.
• Fast for relatively small models. Strong for rapid prototyping.
• Optimized for using some numeric and symbolic approaches, not just Monte Carlo.
• Embeddable in Javascript.
• Free and open-source.

Weaknesses

• Limited scientific capabilities.
• Much slower than serious probabilistic programming languages on sizeable models.
• Can't do Bayesian backwards inference.
• Essentially no support for libraries or modules (yet).
• Still very new, so a tiny ecosystem.
• Still very new, so there are likely math bugs.
• Generally not as easy to use as Guesstimate or Causal, especially for non programmers.