Daniel Andres Pinto Alvarado

Daniel Andres Pinto Alvarado is a software engineering student at Universidad Simón Bolívar. His areas of research are functional programming, domain-specific languages, and type-driven software development. He is currently leading the effort to embed Lilly – the language foundation of ZenSheet – in Web clients.

LinkedIn Profile

Monte Carlo Methods in Haskell and Functional Spreadsheets

Monte Carlo simulations are an important computing technique in science, engineering, and business. Originally employed to perform complex calculations required for the development of nuclear weapons (Manhattan Project), Monte Carlo methods have found multiple uses in fields as diverse as physics, chemistry, telecommunications, virology, marketing, and finance. They are also useful in educational settings, helping students develop statistical intuition and a better understanding of well-known results, like the law of large numbers and the central limit theorem.

We introduce the topic and demonstrate how to implement Monte Carlo simulations in a functional programming language, like Haskell, as well as a higher-order functional spreadsheet, like ZenSheet.