May

29

A Fresh Look at the Kalman Filter

In this paper, we discuss the Kalman filter for state estimation in noisy linear discrete-time dynamical systems. We give an overview of its history, its mathematical and statistical formulations, and its use in applications. We describe a novel derivation of the Kalman filter using Newton's method for root finding. This approach is quite general as it can also be used to derive a number of variations of the Kalman filter, including recursive estimators for both prediction and smoothing, estimators with fading memory, and the extended Kalman filter for nonlinear systems.

Big Al adds:

Forecasting with the Kalman Filter
Mike Mull, PyData Chicago 2016

The Kalman filter is a popular tool in control theory and time-series analysis, but it can be a little hard to grasp. This talk will serve as an introduction to the concept, using an example of forecasting an economic indicator with tools from the statsmodels library.


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