Distributed Solar: The Democratizaton of Energy
Blogroll
- AP Statistics: Sampling, by Michael Porinchak
- International Society for Bayesian Analysis (ISBA)
- distributed solar and matching location to need
- "Impacts of Green New Deal energy plans on grid stability, costs, jobs, health, and climate in 143 countries" (Jacobson, Delucchi, Cameron, et al)
- Thaddeus Stevens quotes
- Mark Berliner's video lecture "Bayesian mechanistic-statistical modeling with examples in geophysical settings"
- Number Cruncher Politics
- Busting Myths About Heat Pumps
- Dollars per BBL: Energy in Transition
- Earth Family Alpha
climate change
- Klaus Lackner (ASU), Silicon Kingdom Holdings (SKH)
- AIP's history of global warming science: impacts
- Sea Change Boston
- Energy payback period for solar panels
- Eli on the spectroscopic basis of atmospheric radiation physical chemistry
- "Lessons of the Little Ice Age" (Farber)
- Isaac Held's blog
- Tuft's Professor Kenneth Lang on the physical chemistry of the Greenhouse Effect
- Sir David King
- Ellenbogen: There is no Such Thing as Wind Turbine Syndrome
Archives
Jan Galkowski
Tag Archives: dp-means
The dp-means algorithm of Kulis and Jordan in R and Python
dp-means algorithm. Think k-means but with the number of clusters calculated. By John Myles White, in R. (Github link off that page.) By Scott Hendrickson, in Python. (Github link off that page.)
Posted in Bayesian, Gibbs Sampling, JAGS, mathematics, maths, R, statistics, stochastic algorithms, stochastic search
Tagged dp-means
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