See https://wordpress.com/view/667-per-cm.net/ Retired data scientist and statistician. Now working projects in quantitative ecology and, specifically, phenology of Bryophyta and technical methods for their study.
Higgs from AIR describing NAO and EA
Stephanie Higgs from AIR Worldwide gives a nice description of NAO and EA in the context of discussing “The Geographic Impact of Climate Signals on European Winter Storms”
In Monte Carlo We Trust
The statistics blog of Matt Asher, actually called the “Probability and Statistics Blog”, but his subtitle is much more appealing. Asher has a Manifesto at http://www.statisticsblog.com/manifesto/.
Why "naive Bayes" is not Bayesian
Explains why the so-called “naive Bayes” classifier is not Bayesian. The setup is okay, but estimating probabilities by doing relative frequencies instead of using Dirichlet conjugate priors or integration strays from The Path.
"Warming Slowdown?" (part 2 of 2)
The idea of a global warming slowdown or hiatus is critically examined, emphasizing the literature, the datasets, and means and methods for telling such. The second part.
"Warming Slowdown?" (part 1 of 2)
The idea of a global warming slowdown or hiatus is critically examined, emphasizing the literature, the datasets, and means and methods for telling such. In two parts.
The great Michael Osborne's latest opinions
Michael Osborne is a genius operative and champion of solar energy. I have learned never to disregard ANYTHING he says. He is mentor of Karl Ragabo, and the genius instigator of the Texas renewable energy miracle.
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