|
Week |
Chapter |
Contents |
| 1 | 1,2 | Introduction. Likelihood, point estimates. |
| 2 | 3, (4,6,12), 8 | Exponential families, sufficiency, Fisher scoring |
| 3 | 9 | Asymptotics. |
| 4 | 5,10 | Bootstrap, nuisance parameters |
| 5 | 13 | Robustness, model distances |
| 6 | 4, 6, 11, 12 | Modeling, complex data structures |
| 7 | Review |
Week |
Notes and handouts |
| 1 | Lecture 1 |
| 2 | Lecture 2 , Lecture 3 |
| 3 | Lecture 4 , Lecture 5 |
| 4 | Lecture 6 , Lecture 7 , Review notes week 1-4 |
| 5 | Lecture 8 , Lecture 9, I , Lecture 9, II |
| 6 | Lecture 10 , Lecture 11 |
| 7 | Lecture 12 , Review 1 |
Week |
Labs and data links |
| 1 | Suggestion: plot normalized log-likelihood and the quadratic approximation for some easy distribution, like Bin(n,x) for large and small n, and for different values of x. |
| 2 | |
| 3 | Homework1 |
| 4 | Homework2: read Lindsey and write a 1 page summary - focusing on something you found particularly interesting. Also, view the example at the end of lecture 6. Compare UMVUE and MLE for estimating exp(-theta) as sample size n increases. Compare both bias and variance. |
| 5 | Solutions Homework1 |
| 6 | Homework3 Due Wed March 3 |
| 7 | Suggested problems to look at 2.10, 3.2, 3.5, 5.2, 5.4, 8.2, 8.3, 8.7. |
You will be notified the result of your exam by email from LADOK (This is done automatically as soon as the exams have been marked an the results are registered..)
The exams will then be kept at the students' office in the Mathematical Sciences building.
Check that the number of points and your grade given on the exam and registered in LADOK coincide.
Complaints of the marking should be written and handed in at the office. There is a form you can use, ask the person in the office.).
The following link will tell you all about the examination room rules at Chalmers: Examination room instructions