Advanced quantitative methods in herd management
2019
Course plan (last updated November 19th)
Morning sessions are from 9:00 to 12, and afternoon sessions are from 13 to 17.
All sessions are in Room A102, Grønnegårdsvej 2.
|
Week
Map |
Tearcher |
| |
Monday
18/11 |
Afternoon |
Welcome and introduction Linear programming
with computer exercises |
Chapters 1, (3 & 4)
Chapter 10 (you can ignore 10.4.2) |
47 |
DBJ ARK
|
| |
Wednesday 20/11 |
Morning |
Introduction to linear algebra
Relevant statistics: Introduction to the
multivariate normal distribution |
(Appendix C) (Appendix D.1-D.3) |
LVDK ARK |
| |
Wednesday 20/11 |
Afternoon |
From registration to
information +
Computer exercises |
Chapters 2, (5),
6 |
ARK |
| |
Monday 25/11 |
Afternoon |
Introduction to Mandatory Report 1
Relevant
statistics: conditinal probabilities and Baye's
theorem
Bayesian networks I +
Computer exercises: Bayesian networks |
(Appendix A.1)
Jensen (2001), Chapter 1, page 3-28 |
48 |
ARK ARK |
|
Wednesday 27/11 |
Morning |
Bayesian networks: Case example
Bayesian networks II |
(Jensen
et al., 2009) Jensen (2001), Chapter 2, page
35 - 62 |
LVDK ARK |
| |
Wednesday 27/11 |
Afternoon |
Exercises +
work on mandatory report |
|
ARK |
| |
First mandatory report |
| |
Monday 2/12 |
Afternoon |
Introduction to Mandatory
Report 2
Relevant statistics: the
normal distribution and confidence intervals
Monitoring and data filtering - Classical
methods I
Computer exercises: Classical methods I |
Appendix A.3.2 &
A.5.1
Chapter 7.1 - 7.6 |
49 |
DBJ LVDK
DBJ |
| |
Wednesday 4/12 |
Morning |
Guest lecture: IQinABox
Monitoring and data filtering - Classical
methods II |
Chapter 7.7 - 7.8 |
TNM |
| |
Wednesday 4/12 |
Afternoon |
Exercises +
work on mandatory report |
|
DBJ |
| |
Second mandatory report |
| |
Monday 9/12 |
Afternoon |
Introduction to Mandatory report 3
Relevant statistics: autocorrelation
Monitoring and data filtering - DLM I
Computer exercises
- DLM |
Chapter 7.6.1
Chapter 8.1 - 8.2 |
50 |
DBJ LVDK
DBJ |
| |
Wednesday 11/12 |
Morning |
Monitoring and filtering: case study
Monitoring and data filtering - DLM II |
Jensen et al., (2016) 8.3 - 8.4 |
LVDK DBJ |
| |
Wednesday 11/12 |
Afternoon |
Exercises +
work on mandatory report |
|
DBJ
|
| |
Third mandatory report |
| |
Monday 16/12 |
Afternoon |
Introduction to Fourth Mandatory Report
Relevant statistics: Matrices and
conditional probability
Markov decision
processes I
Markov decision processes: Computer exercises |
Appendix C.2 & A.4
Chapter 13.1-13.2 |
51 |
DBJ ARK
DBJ |
| |
Wednesday 18/12 |
Morning |
Markov
decision processes: Case example
Markov decision processes II
Markov decision processes: Computer exercises |
Kristensen & Søllested, 2004a+b
Chapter 13.3 - 13.6. |
LVDK DBJ |
| |
Wednesday 18/12 |
Afternoon |
Exercises +
work on mandatory report |
|
DBJ |
| |
Fourth mandatory report |
| |
|
|
Christmas break |
HAPPY CHRISTMAS! |
52 |
(self) |
| |
|
|
Decisions and strategies (self-study) |
Chapter 9 |
1 |
(self) |
| |
Monday 6/1 |
Afternoon |
Discussion of oral
exam Decision graphs I
Decision graphs: Computer exercises I |
Chapter 12
|
2 |
DBJ/ARK ARK
ARK |
| |
Wednesday 8/1 |
Morning |
Guest lecture: SEGES Decision
graphs II
Decision graphs: Computer exercises II |
Chapter 12, Jensen (2001, Section
7.6)
|
KND ARK
ARK |
| |
Wednesday 8/1 |
Afternoon |
Exercises |
|
ARK |
| |
Monday 13/1 |
Afternoon |
Relevant statistics - various
probability distributions
Simulation I
Simulation: Computer exercises I |
Appendix A.2 - A.4
Chapter 14 |
3 |
LVDK DBJ |
| |
Wednesday 15/1 |
Morning |
Simulation: Case example
Simulation II
Simulation: Computer exercises II |
Ettema et al. (2010)
Chapter 14 |
LVDK
DBJ |
| |
Wednesday 15/1 |
Afternoon |
Exercises |
|
DBJ |
| |
(prepare for
exam) |
| |
Monday 20/1 |
Afternoon |
No teaching (prepare for exam) |
|
4 |
(self) |
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Wednesday 22/1 |
Morning |
No teaching (prepare for exam) |
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| |
Wednesday 22/1 |
Afternoon |
No teaching (prepare for exam) |
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| |
Friday 24/1 |
EXAM |
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DBJ/ARK |
| |
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Mondays |
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Wednesdays, morning |
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Friday, exam |
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Wednesdays, afternoon |
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Home work |
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Teachers
- DBJ
-
Dan Børge Jensen,
Department of Veterinary and Animal Sciences, UCPH
- ARK
-
Anders Ringgaard Kristensen,
Department of Veterinary and Animal Sciences, UCPH
- LVDK
-
Leonardo Victor de Knegt, Department of
Veterinary and Animal Sciences, UCPH
- TNM
- Thomas Nejsum Madsen, IQinABox
- KND
- Katarina Nielsen Dominiak, SEGES
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