Fall 2019 STATISTICAL COMPUTING

Instructors: Hyokyoung Grace Hong (hhong@msu.edu) & Gustavo de los Campos (gustavoc@msu.edu)

Syllabus

Time & Place M/W 3:00 PM - 4:20 PM. NEW ROOM: Wells Hall B110F

Office hours Dr. Hong: Wells Hall C435; M, W 1-2P Or By appointment.

Dr. de los Campos: TBA

Modules

Module 1 (Introduction, 2.5 weeks)

1. R Studio/R Markdown
2. Introduction to R
3. Data preparation, loops, conditional statements, Inclass assignment 0

Reference: Advanced R

Module 2 (Statistical Models, 4 weeks)

1. Linear regression models (Inclass assignment 1: Due 9/11)
2. Generalized linear models (Inclass assignment 2: Due 9/18)
3. Variable screening methods (Inclass assignment 3: Due 9/25)
4. Survival models (Inclass assignment 4: Due 10/2)

Exam 1 (October 14)

Module 3 (Maximum Likelihood)

1. Maximization using general purpose optimization algorithms
2. The EM-Algorithm
3. Regularized regression methods

Module 4 (Monte Carlo Methods)

1. Sampling Random Variables
2. Power Analysis

Module 5 (Resampling methods)

1. Bootstrap (application: SEs for odds ratios in logistic regression)
2. Permutation test (p-values for odds ratios in logistic regression)

Module 6 (Embedding C/C++ code into R, tentative)

Homeworks

HW1 HW2 Hw2_sol

Datasets

Crab