exercises for Thu Feb 3

1. On Thu Jan 27, in a somewhat dark Aud. 4 due to the fire in the herretoalettomr?de three days earlier, we went through these exercises: 1.4, 1.6, 1.20; proving formula (1.35), with implications for the case of \rho(h) = \rho^j; initial regression modelling attempts for the JJ dataset.

2. We then discussed central concepts and methods from Ch 1, with emphasis on the covariance function \gamma(h) and correlation function \rho(h), and their empirical counterparts, the important acf(xdata) algorith. In particular, theory was given to explain what happens with the acf in the case of i.i.d. data.

3. I'm placing my R script com1d on the website, with regression things for the JJ dataset. Run its different parts, make sure you understand what they accomplish, and play with variations.

4. For Thu Feb 3, first try out a couple of more regression models for the JJ dataset, perhaps taking my com1d as point of departure. Include a cyclic term for the trend function. Then do exercises 1.7, 1.8, 1.10, 1.14, 1.16 from the book.

5. I am writing up a few Exercises and Lecture Notes things, and will post the first version of these on the course site within a few days.