I have a similar question to the one in the link below:

Intuitive explanation of state space models

In the link they recommend the book by Commandeur and Koopman. I have this book already.

I was looking for something that is introductory like this book but takes things further to include non gaussian stats space models.

Does anyone know of online set of lecture notes that does this?
I have searched the net but most courses only seem to offer a chapter here and there on state space models?
I want a set of notes that focuses on state space models and goes into some depth say 50+ pages? As well as the mathematics I want a set of notes that provides the intuition as well as giving the pros/cons when comparing it to other approaches?
I have searched extensively but can't find what I want.
Can someone please point me in the right direction?


Bayesian Filtering and Smoothing by Simo Särkkä is one of my favorites. It's all about state space models. It starts with high-level discussion of the modeling philosophy and domains of application. It then works its way from linear, Gaussian systems and the Kalman filter to the advanced Monte Carlo techniques that are used for non-linear and non-Gaussian systems. I don't think you'll find much "giving the pros/cons when comparing it to other approaches." But otherwise, give it a whirl.

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