TY - UNPB
T1 - Osband's Principle for Identification Functions
AU - Dimitriadis, Timo
AU - Fissler, Tobias
AU - Ziegel, Johanna
PY - 2022
Y1 - 2022
N2 - Given a statistical functional of interest such as the mean or median, a (strict) identification function is zero in expectation at (and only at) the true functional value. Identification functions are key objects in forecast validation, statistical estimation and dynamic modelling. For a possibly vector-valued functional of interest, we fully characterise the class of (strict) identification functions subject to mild regularity conditions.
AB - Given a statistical functional of interest such as the mean or median, a (strict) identification function is zero in expectation at (and only at) the true functional value. Identification functions are key objects in forecast validation, statistical estimation and dynamic modelling. For a possibly vector-valued functional of interest, we fully characterise the class of (strict) identification functions subject to mild regularity conditions.
U2 - 10.48550/arXiv.2208.07685
DO - 10.48550/arXiv.2208.07685
M3 - Working Paper/Preprint
BT - Osband's Principle for Identification Functions
ER -