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Estimability of the linear effects in state space models with an unknown initial condition
Author(s) -
Selukar Rajesh
Publication year - 2010
Publication title -
journal of time series analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.576
H-Index - 54
eISSN - 1467-9892
pISSN - 0143-9782
DOI - 10.1111/j.1467-9892.2010.00653.x
Subject(s) - mathematics , state (computer science) , state space , kalman filter , linear model , simple (philosophy) , space (punctuation) , mathematical optimization , state space representation , algorithm , statistics , computer science , philosophy , epistemology , operating system
In the case of state space models with an unknown initial condition, the diffuse Kalman smoother can be used to obtain smoothed state estimates. When the full initial state is not estimable because the available data are insufficient, some linear combinations of the states can still be estimable. This brief note provides a simple method to determine whether a linear combination of a state is estimable.