We learn R from scratch.

Examination

• PLEASE NOTE THAT THE ORIGINAL EXAMINATION HAD A MINOR ERROR THAT HAS NOW BEEN CORRECTED. PLEASE DOWNLOAD THE EXAM AGAIN USING THE LINK BELOW
• Also note that I will allow up to 3 written pages instead of 2. Trace plots will not count towards the 3 page limit.
• The examination will be an assignment. It is due on July 1. You may submit it to me in room 219, building 4 Shahe Campus. Instructions are included here. The dataset for the first part is here. The dataset for the second part is here. Both datasets can be opened in R using the load command.
• If you have any questions you can email me or ask me in class. Good luck!

Lecturers

• Feng Li, Central University of Finance and Economics
• Anastasios Panagiotelis, Monash University

Literature

• An Introduction to R
• Jones, Owen, Robert Maillardet, and Andrew Robinson. Introduction to scientific programming and simulation using R. CRC Press, 2014.

Lecture notes

• Introduction| Lab
• Data manipulation| Lab
• Loops and Functions | R Code
• Vectorization
• Distributions and Random Numbers | R Code
• R Graphics | R Code
• Optimization | Matrix Derivatives | R Code: Root Finding | R Code: Multidimensional Newton’s Method|Notes: Logistic Regression | R Code: Logistic Regression|Comparison |Nelder Mead
• Simulation: Lecture Notes (Tue) | Simulation: Exercises (Fri) |R Code: Lectures (Tue) |R Code: Exercises (Fri)
• Markov chain Monte Carlo | R Code (Markov Chains)
• Bayesian Inference | Bayesian Inference (Computer Lab)|Bayes Inference (Solutions) |Computing on the Log Scale
• Application of MCMC (Lecture Notes) | R Code (MCMC)|Gibbs Sampler (R Code)
• Examination Practice Question (to be completed in class)
• Review