Dates: Monday, January 26 - Friday, January 30, 2015
Morning Session | 9:30am - 10:30am
Afternoon Session | 1:30pm - 2:30pm
Location: Sherrerd Hall 101
led by Hubert Jin, Senior Research Specialist
The advanced statistical programming camp builds on the introductory statistical programming camp by expanding the computing toolsets of researchers. The camp shows how to analyze big datasets (e.g., voter files across many states, micro-level international trade data, large federal personnel databases) and employ computationally intensive methods (e.g., Monte Carlo simulations, Bayesian Markov chain Monte Carlo, cross-validation, or bootstrap). We begin by introducing some low-cost strategies for improving performance in R. To help process large data and improve the speed of computation, we then cover parallel execution of R code on both personal machines and on remote high performance computing systems available at Princeton. Lastly, we cover basic C++ and the use of Rcpp to produce tightly integrated and fast compiled code.
If you are interested in attending this workshop, you must register. Please sign up here. You will be added to the Blackboard class which will give you access to materials and the discussion board.