COMPUTATIONAL STATISTICS (MA 6973, MATH 2080)
Fall 2021
Instructor
Mike O'Neil (oneil@cims.nyu.edu)

Teaching assistant
Paul Beckman (pgb8409@nyu.edu)

Description
This course aims to cover topics needed to develop a broad working knowledge of modern computational statistics. We seek to develop a practical understanding of how and why existing methods work, enabling effective use of modern statistical methods. Achieving these goals requires familiarity with diverse topics in statistical computing, computational statistics, computer science, and numerical analysis. View the syllabus for more detailed information.

Lecture
Wednesday 11:00am - 1:30pm, 2 MTC 804
(In person)

Office hours
By appointment

Announcements
None.

Materials
The course will work off of the material from two textbooks:

- Efron and Hastie, Computer Age Statistical Inference, Cambridge, 2016
- Gentle, Computational Statistics, Springer, 2009

Both texts are available for free via NYU Libraries.

Grading
A final numerical grade will be computed basic on the following rubric:

10% Homework 1
10% Homework 2
10% Homework 3
10% Homework 4
30% Midterm
30% Final project
The overall letter grade will be computed based on the overall numerical grade.

Schedule
Below is an updated list of discussion topics along with any documents that were distributed, notes, or relevant code.
Date Topics Materials
Sep 8 Probability and statistics review Notes
Efron & Hastie: Ch 1-5
Gentle: Ch 1
Sep 15 Root finding, optimization Notes
Gentle: Ch 6.1-6.2
Sep 22 BFGS
Numerical linear algebra:
Operation counts, norms, and conditioning
Notes
Gentle: 6.2
Steven Johnson Notes
Gentle: Ch 2, 3, 5.1
Sep 29 Numerical linear algebra:
LU, Cholesky, least squares, QR
Notes
Gentle: Ch 5.2-5.3, 5.6
Oct 6 Singular value decomposition
Principal component analysis
Notes
Gentle: Ch 1.2, 16.3
Oct 13 Gaussian processes Notes
Rasmussen and Williams
Oct 20 Midterm (In class)
Oct 27
Nov 3
Nov 10
Nov 17
Nov 24
Dec 1
Dec 8 Project presentations