"… [We] can easily handle this problem, in practice; it will be a closely run race, the race of our lives. I like to say never underestimate technology and never underestimate … [our] … ability … to screw it up. " — Jeremy Grantham
While it is described as “The mathematical (and other) thoughts of a (now retired) math teacher”, this is false humility, as it chronicles the present and past life and times of mathematicians in their context. Recommended.
Darren Wilkinson's introduction to ABC
Darren Wilkinson’s introduction to approximate Bayesian computation (“ABC”). See also his post about summary statistics for ABC https://darrenjw.wordpress.com/2013/09/01/summary-stats-for-abc/
I have used dlm almost exclusively, except when extreme efficiency was required. Since Jouni Helske's KFAS was rewritten, though, I'm increasingly drawn to it, because the noise sources it supports are more diverse than dlm's. KFAS uses the notation and approaches of Durbin, Koopman, and Harvey.
``The real problem is that programmers have spent far too much time worrying about efficiency in the wrong places and at the wrong times; premature optimization is the root of all evil (or at least most of it) in programming.'' Professor Donald Knuth, 1974