Week 5

Question 1

Quickly explain the SDPK model.

Answer 1

Question 2

Derive the MC-estimator of the SDPK model.

Answer 2

Question 3

What is the MC-estimator of the SDPK-model?

Answer 3

Question 4

How does signal extraction work when using importance sampling and the SPDK-method? What are the four steps?

Answer 4

Question 5

How are importance weights defined (please state the entire equation)? What do they represent?

Answer 5

Question 6

When does the MC-estimator converge to the true expectation?

Answer 6

Question 7

Construct MC-estmators for these two.

Answer 7

Question 8

How does parameter estimation work when using importance sampling and the SPDK-method? What are the four steps?

Answer 8

Question 9

What is the goal of particle filtering? Why?

Answer 9

Question 10

What are the two main things that happen in a particle filter?

Answer 10

Question 11

What do we set g(.|.) for the bootstrap filter?

Answer 11

Question 12

What is the Monte Carlo estimator of the Bootstrap-filter?

Answer 12

Question 13

What is the concept of Degeneracy? How is it connected to resampling?

Answer 13

Question 14

What are the five steps of the Bootstrap filter?

Answer 14