Why Kalman Filter?
2018
Snyder, R. D.
In this paper the Kalman filter and regression approaches for estimating linear state space models are compared. It is argued that the Kalman filter is no more efficient from a computational point of view, is relatively more complex and hence more obtruse, and that as consequence its central role in the smoothing, estimation and prediction of time series is questionable.
Show more [+] Less [-]Bibliographic information
This bibliographic record has been provided by University of Minnesota
