State-Space Models and Filtering
Kalman and particle filters for hidden-state inference.
State-Space Models and Filtering. Kalman and particle filters for hidden-state inference.
Foundations and canonical references
The standard treatments of state-space models and filtering approach the subject from complementary angles. Durbin, Time Series Analysis by State Space Methods (2012) is the anchor reference for the subject and lays out the core definitions, theorems, and worked examples that practitioners return to.
Open methodological questions for state-space models and filtering include sharpening the bridges between foundational theory and computational practice, extending classical results to broader or more structured settings, and integrating the techniques surveyed above with adjacent mathematical disciplines. The references listed in this page are the entry points that current work builds on.
Prerequisites
Sources
- textbook · primary · 2012Time Series Analysis by State Space Methodsdurbin-2012, koopman-2012
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