Tyler Ransom

Computer Code

Julia

• Introductory slides that introduce Julia (outdated version here)
• My Github repository, which introduces basic econometric models in Julia.
• EM algorithm example: Code to generate data and estimate simple versions of the EM algorithm for estimation of models with discrete type-specific unobserved heterogeneity.

Matlab

• summarize.m: Mimics Stata's summarize command.
• normalMLE.m: Estimates normal linear regression with heteroskedastic errors by maximum likelihood.
• applyRestr.m: Allows for easy parameter restrictions in optimization problems (co-writen with Jared Ashworth).
• clogit.m: Estimates conditional logit regression by maximum likelihood (co-writen with Jared Ashworth).
• ologit.m: Estimates the ordered logit model by maximum likelihood.
• EM algorithm example: Code to generate data and estimate simple versions of the EM algorithm for estimation of models with discrete type-specific unobserved heterogeneity.

LaTeX

• Cape Town: a Beamer slide theme for LaTeX presentations.
• Poster: a LaTeX poster example.
• jole.bst: a BibTeX style file for formatting citations according to the style of the Journal of Labor Economics.
• CV template: a template for producing a CV in LaTeX (PDF output)
• Template for completing peer review: a template for producing materials for requests to serve as a peer reviewer

Machine Learning Resources

• Introduction to machine learning for social scientists: Slides from a short presentation that outlines what machine learning is and how social scientists can benefit from using its methods.
• Practical tips for machine learning practitioners, via Pedro Domingos.
• The Master Algorithm, written by Pedro Domingos.