1
Q
Assumptions of SLRM
A
2
Q
Invariance property of MLE
A
3
Q
Consistency of a parameter
A
4
Q
justifyMLE as point estimator
A
5
Q
If a likelihood fx has unique maximum then
A
And this is the MLE
6
Q
Score function
A
Gradient is taken WRT values of θ
7
Q
(Strong) likelihood principle
A
8
Q
Define the observed information matrix
A
Where p is dim of θ hence it becomes θ
9
Q
How do you use score function and observed information matrix with MLE
A
MLE is solution to score function = 0
You can use the information matrix to determine if the inflection point is a maximum using second deriv
KCL Statistical Inference
flashcards
Decks in class (12)
# Cards
