CS (frmr Stat) Prof, UC Davis. Views mine, not UCD's. Political progressive, but not "woke" and hate sloppy thinking of any stripe. Admirer of 长乐路.
Dec 24, 2023 • 20 tweets • 3 min read
#rstats Here I will first introduce the concept of quantile regression (QR), a powerful technique that is rarely taught in stat courses. I’ll give an example from the quantreg package, and then will show how qeML can be used to do model-free QR estimation. 1/
Along the way, I will also illustrate the use of closures in R.
Notation: We are predicting a scalar Y (including the case of dummy/one-hot variables) from a feature vector X. 2/
Jun 25, 2021 • 13 tweets • 4 min read
#Statistics#math#rstats Please read this if you are a California professor in a STEM field. 1/
The California Dept. of Education (CDE) is considering a radical redesign of K-12 math education, both in terms of curricula but also in terms of methods of instruction. 2/
May 23, 2019 • 17 tweets • 4 min read
#rstats for YOU: Ever encountered an R error message like "Couldn't create memory segment of size 3.2G"? Also, more subtly, ever had some code run slowly in spite of little apparent reason? And ever wonder why data.table is so blindingly fast? This post will be on MEMORY. 1/n
So here goes Memory 101A. Memory (meaning RAM) is broken down into "words," typically 8 bytes long. One R numeric quantity will occupy one word. So, e.g. 1 gig of memory will hold a numeric vector of length only 125 million. 2/n
