Instructor: Suhasini Subba Rao (office: Blocker 432).
Here is the Handout
Homework 1: 1.1-1.6 (Due Friday 9th Sept).
Homework 2: 1.7-1.9, 2.1 and 2.4 (Due Friday 16th Sept).
This piece of code generates an uncorrelated linear time series.
This piece of code generates causal and noncausal AR(1) and AR(2) time series.
This piece of code generates causal AR(2) time series, where the roots of the corresponding characteristic polynomial are complex.
Homework 3: The remaining HW questions in Chapter 2 (Due Monday 26th Sept). This is the code for some of the simulations code for this HW.
Please note that due to the Big Data workshop the class on (Friday) 23rd September is cancelled.
Homework 4: All problems in Chapter 3 (3.1-3.7). Due October 7th.
For chapter 4 we will consider nonlinear time series models. Here is the code for various models
Nonlinear Time Series (Chapter 4) (these may be edited)
Homework 5: All problems in Chapter 4. Due October 24th.
The sample mean and covariance (Chapter 6) (these may be edited).
Homework 6: All problems in Chapter 5. Due October 31st (Exercise 5.4 is optional but fun).
Homework 7: All problems in Chapter 6. Due November 11th.
Parameter estimation (Chapter 7)
Here is a chapter on conditional expectations (taken from Stochastic Limit Theorem, by James Davidson). Please look at Theorem 10.26 (on conditional expectations for nested sigma-algebras).