Ultimate goal of statistics is data analysis. E.g., PageRank, handwritten digit recognization, Netflix matrix completion, ...
Statistics is partly empirical and partly mathematical. It is now almost entirely computational.
Kenneth Lange
Statisticians used to .. | Now we spend all time ... |
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Two essential skills for modern statisticians: programming and computational algorithms.
Data Scientist (n.): Person who is better at statistics than any software engineer and better at software engineering than any statistician.
Josh Willis on Twitter
Numerical linear algebra
Optimization
Convex programming (LS, LP, QP, GP, SOCP, SDP). Download and study Stephen Boyd's book, watch lecture vides or take UCLA EE236B by Vandenberghe, familiarize yourself with the good optimization softwares. Convex programming is becoming a technology, just like least squares (LS). Browse the documentation of cvx
and Convex.jl
to see which functions are implemented.
Generic nonlinear optimization tools: Newton, Gauss-Newton, quasi-Newton, (nonlinear) conjugate gradient, ...
Optimization tools developed by statisticians: Fisher scoring, EM, MM, ... Take UCLA Biomath 210 by Kenneth Lange for a thorough study of MM algorithms.
Kenneth Lange is teaching a new course in 2017 Fall.
Biomath 205: Top Computational Algorithms.
Enjoy (or hate) Julia?
JuliaCon 2017 at UC Berkeley: http://juliacon.org/2017/