Statements (29)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:mathematical_concept
|
| gptkbp:appearsIn |
asymptotic theory of statistics
|
| gptkbp:appliesTo |
multivariate parameter estimation
|
| gptkbp:component |
gptkb:Fisher_information
|
| gptkbp:describes |
amount of information a random variable carries about an unknown parameter
|
| gptkbp:field |
gptkb:information_theory
statistics |
| gptkbp:heldBy |
symmetric matrix
expected value of the observed information matrix positive semi-definite matrix matrix of second derivatives of the log-likelihood function |
| https://www.w3.org/2000/01/rdf-schema#label |
Fisher information matrix
|
| gptkbp:namedAfter |
gptkb:Ronald_Fisher
|
| gptkbp:notation |
I(θ)
|
| gptkbp:relatedTo |
score function
covariance matrix likelihood function |
| gptkbp:usedFor |
gptkb:Cramér–Rao_bound
estimating variance of estimators |
| gptkbp:usedIn |
gptkb:machine_learning
gptkb:signal_processing biostatistics physics econometrics maximum likelihood estimation parameter estimation |
| gptkbp:bfsParent |
gptkb:Rao–Cramer_inequality
gptkb:Natural_Policy_Gradient |
| gptkbp:bfsLayer |
8
|