Quantitative Finance

Statistical Computing in R

Heuristic Optimization

About Burns statistics

Specialties include:

  • Programming in the R language
  • Statistics, including quantitative finance
  • Solving difficult problems via heuristic optimization (genetic algorithms and simulated annealing).

Consulting

Pat has worked, mainly in finance, for over thirty years both as a consultant and an employee. We are currently not in the market for new consulting jobs.

Software development

Pat was a lead developer of S-PLUS, the precursor to the R language, in its early years. His tasks included adding functionality (such as principal components and robust estimation in several settings), finding and fixing bugs, and documentation. He has been a user of R for over 25 years.

Essential reading

By Patrick Burns

The R Inferno

Navigating the hidden pitfalls and logical circles of the R programming environment.

Tao Te Programming

A philosophical exploration of the craftsmanship behind high-
stakes quantitative code.

Additional reading

S Poetry

An earlier publication exploring the transition from S to R. Included for readers interested in the language’s history.

Blog

Recent explorations in finance, statistics, and the peculiar intricacies of computing.

  • jun 25, 26

    The joy of data analysis

    Music and snow. Poke my eyes out Perhaps your immediate response is: ”I’d rather poke my eyes out with a burning stick than do data analysis.” There’s a completely different [...]

  • jun 25, 26

    A first step towards R from spreadsheets

    Move your data analysis to a computing environment specifically designed for it. Why R and not spreadsheets? Here are three reasons: complexity graphics money Spreadsheets are easily overwhelmed.  Very complex [...]

  • jun 25, 26

    An R debugging example

    The steps taken to fix an R problem. Task To prepare for the Portfolio Probe blog post called ”Implied alpha and minimum variance”, I tried to update a matrix of [...]