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← 667-per-cm.net, the Podcast: Episode 1.

The Johnson-Lindenstrauss Lemma, and the paradoxical power of random linear operators. Part 1. →

667-per-cm.net, the Podcast: Episode 2, or Probability is Real.

Posted on 18 November 2018 by ecoquant

This is the second installment of the Podcast here, hopefully with better sound quality.

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← 667-per-cm.net, the Podcast: Episode 1.

The Johnson-Lindenstrauss Lemma, and the paradoxical power of random linear operators. Part 1. →

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Kalman filtering and smoothing; dynamic linear models

Also, see datasets and R examples to accompany this excellent text.

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
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