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Course content and schedule

Only parts of the material in the books will be covered. Both books are recommended bying, as they are excellent reference litterature. Both books are available as E-books free of charge.

The background material is treated in Casella and Lehmann chapters 1.2-1.3; students that feel uncertain on whether they have sufficient backgroud should consult these pages. More detailed background information on measure theory and topology can be found here.

 

LectureDate and placeContentMaterial
119/3, MH227Overview. The inference problem. Casella and Lehmann 1.1, Notes-Lecture1
222/3, MH227Group families. Exponential families. 1.4-1.5, Notes-Lecture2
326/3, MH227Exponential families.  1.5 1.7, Notes-Lecture3 
428/3, MH228Sufficiency.  Convex loss functions. UMVU estimation.1.6-1.7, 2.1, Notes-Lecture4
5NOTE, 19/4, MH227,10:15-12:00UMVU estimation. Continuous and discrete problems.2.2, 2.3, Notes-Lecture5
6NOTE, 19/4, MH229, 15:15-17:00Equivariance.

Notes-Lecture 6,

3.2, 3.1, Lecture notes on Equivariance.

7NOTE, 23/4, 15:15-17:00  MH227Location and location-scale equivariance.3.3
826/4, MH227Bayesian inference. 4.1
930/4, MH227Bayesian inference. Single prior bayes.4.1, 4.2
1028/4, MH227, cancelled5, Lecture notes on Minimax estimation. (Updated May 11, 2014.)
113/5, MH227, cancelled
127/5, MH227

Lecture Notes on Decision theory. (Updated May 27, 2014.) Notes-Lecture8

 

139/5, MH2283.1, 3.2, 3.3. Notes-Lecture9, Notes-Lecture10
1414/5, MH2273.3, 3.5, Notes-Lecture 11
1517/5, MH3333.3, 3.4, 3.5, Notes-Lecture12, Notes-Lecture13, Notes-Lecture14
1621/5, MH227Notes-Complements 3.3, 3.4, 3.5, Notes-Lecture15, Notes-Lecture16
1723/5, MH227Notes-Lecture17, Notes-Lecture18, Notes-Lecture19
ExerciseDate and placeTheoryExercise number
122/3, MH227The inference problem. Group families. 1.2, 1.10, 2.11, 4.1, 4.5, 4.13, 4.14 
2            28/3, MH227Exponential families.5.1, 5.10, 5.12, 5.13, 1.10
3NOTE, 23/4, MH227, 10:15-12:00

Sufficient statistics.

1.4, 4.2, 5.2, 6.2, 6.5

 

 

4

26/4, MH227

Sufficient statistics, convex loss functions.6.6, 6.16, 7.10
53/5, MH227
69/5, MH227
717/5, MH227
823/5, MH227
Sidansvarig: webbansvarig@math.lu.se | 2018-05-24