Distributed Solar: The Democratizaton of Energy
Blogroll
- Leadership lessons from Lao Tzu
- Earle Wilson
- Gavin Simpson
- 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/.
- Tim Harford's “More or Less'' Tim Harford explains – and sometimes debunks – the numbers and statistics used in political debate, the news and everyday life
- Mertonian norms
- All about models
- Risk and Well-Being
- Peter Congdon's Bayesian statistical modeling Peter Congdon’s collection of links pertaining to his several books on Bayesian modeling
- Mike Bloomberg, 2020 He can get progress on climate done, has the means and experts to counter the Trump and Republican digital disinformation machine, and has the experience, knowledge, and depth of experience to achieve and unify.
- "Talking Politics" podcast David Runciman, Helen Thompson
- Simon Wood's must-read paper on dynamic modeling of complex systems I highlighted Professor Wood’s paper in https://hypergeometric.wordpress.com/2014/12/26/struggling-with-problems-already-attacked/
- Mrooijer's Numbers R 4Us
- Why It’s So Freaking Hard To Make A Good COVID-19 Model Five Thirty Eight’s take on why pandemic modeling is so difficult
- Subsidies for wind and solar versus subsidies for fossil fuels
- Woods Hole Oceanographic Institution (WHOI)
- Giant vertical monopolies for energy have stopped making sense
- "Consider a Flat Pond" Invited talk introducing systems thinking, by Jan Galkowski, at First Parish in Needham, UU, via Zoom
- John Cook's reasons to use Bayesian inference
- Survey Methodology, Prof Ron Fricker http://faculty.nps.edu/rdfricke/
- Mark Berliner's video lecture "Bayesian mechanistic-statistical modeling with examples in geophysical settings"
- Ives and Dakos techniques for regime changes in series
- All about ENSO, and lunar tides (Paul Pukite) Historically, ENSO has been explained in terms of winds. But recently — and Dr Paul Pukite has insisted upon this for a long time — the oscillation of ENSO has been explained as a large-scale slosh due to lunar tidal forcing.
- Dollars per BBL: Energy in Transition
- What If
- Slice Sampling
- Awkward Botany
- Professor David Draper
- Ted Dunning
- Fear and Loathing in Data Science Cory Lesmeister’s savage journey to the heart of Big Data
- Earth Family Alpha Michael Osborne’s blog (former Executive at Austin Energy, now Chairman of the Electric Utility Commission for Austin, Texas)
- BioPython A collection of Python tools for quantitative Biology
- WEAPONS OF MATH DESTRUCTION, reviews Reviews of Cathy O’Neil’s new book
- Pat's blog 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.
- Thaddeus Stevens quotes As I get older, I admire this guy more and more
- Bob Altemeyer on authoritarianism (via Dan Satterfield) The science behind the GOP civil war
- distributed solar and matching location to need
- John Kruschke's "Dong Bayesian data analysis" blog Expanding and enhancing John’s book of same title (now in second edition!)
- Comprehensive Guide to Bayes Rule
- Gabriel's staircase
- Dr James Spall's SPSA
- Logistic curves in market disruption From DollarsPerBBL, about logistic or S-curves as models of product take-up rather than exponentials, with notes on EVs
- Dominic Cummings blog Chief advisor to the PM, United Kingdom
- All about Sankey diagrams
- Leverhulme Centre for Climate Change Mitigation
- The Mermaid's Tale A conversation about biological complexity and evolution, and the societal aspects of science
- "Perpetual Ocean" from NASA GSFC
- The Plastic Pick-Up: Discovering new sources of marine plastic pollution
- James' Empty Blog
- Number Cruncher Politics
climate change
- James Hansen and granddaughter Sophie on moving forward with progress on climate
- Energy payback period for solar panels Considering everything, how long do solar panels have to operate to offset the energy used to produce them?
- World Weather Attribution
- Tamino's Open Mind Open Mind: A statistical look at climate, its science, and at science denial
- Transitioning to fully renewable energy Professor Saul Griffiths talks to transitioning the customer journey, from a dependency upon fossil fuels to an electrified future
- Documenting the Climate Deniarati at work
- Interview with Wally Broecker Interview with Wally Broecker
- Skeptical Science
- HotWhopper: It's excellent. Global warming and climate change. Eavesdropping on the deniosphere, its weird pseudo-science and crazy conspiracy whoppers.
- Climate model projections versus observations
- ATTP summarizes all that stuff about Committed Warming from AND THEN THERE’S PHYSICS
- The Carbon Cycle The Carbon Cycle, monitored by The Carbon Project
- And Then There's Physics
- Paul Beckwith Professor Beckwith is, in my book, one of the most insightful and analytical observers on climate I know. I highly recommend his blog, and his other informational products.
- Reanalyses.org
- SOLAR PRODUCTION at Westwood Statistical Studios Generation charts for our home in Westwood, MA
- Rabett Run Incisive analysis of climate science versus deliberate distraction
- Wally Broecker on climate realism
- David Appell's early climate science
- Bloomberg interactive graph on “What's warming the world''
- Mrooijer's Global Temperature Explorer
- The Sunlight Economy
- History of discovering Global Warming From the American Institute of Physics.
- Ellenbogen: There is no Such Thing as Wind Turbine Syndrome
- The net average effect of a warming climate is increased aridity (Professor Steven Sherwood)
- "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.
- Équiterre Equiterre helps build a social movement by encouraging individuals, organizations and governments to make ecological and equitable choices, in a spirit of solidarity.
- The Keeling Curve The first, and one of the best programs for creating a spatially significant long term time series of atmospheric concentrations of CO2. Started amongst great obstacles by one, smart determined guy, Charles David Keeling.
- Agendaists Eli Rabett’s coining of a phrase
- weather blocking patterns
- Climate change: Evidence and causes A project of the UK Royal Society: (1) Answers to key questions, (2) evidence and causes, and (3) a short guide to climate science
- Warming slowdown discussion
- `The unchained goddess' 1958 Bell Telephone Science Hour broadcast regarding, among other things, climate change.
- Wind sled Wind sled: A zero carbon way of exploring ice sheets
- Updating the Climate Science: What path is the real world following? From Professors Makiko Sato & James Hansen of Columbia University
- Earth System Models
- The Scientific Case for Modern Human-caused Global Warming
- Social Cost of Carbon
- The beach boondoggle Prof Rob Young on how owners of beach property are socializing their risks at costs to all of us, not the least being it seems coastal damage is less than it actually is
- Climate Change Denying Organizations
- `Who to believe on climate change': Simple checks By Bart Verheggen
- "Lessons of the Little Ice Age" (Farber) From Dan Farber, at LEGAL PLANET
- Nick Bower's "Scared Scientists"
- Sea Change Boston
- "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.
- Dessler's 6 minute Greenhouse Effect video
- All Models Are Wrong Dr Tamsin Edwards blog about uncertainty in science, and climate science
- Steve Easterbrook's excellent climate blog: See his "The Internet: Saving Civilization or Trashing the Planet?" for example Heavy on data and computation, Easterbrook is a CS prof at UToronto, but is clearly familiar with climate science. I like his “The Internet: Saving Civilization or Trashing the Planet” very much.
- Thriving on Low Carbon
- “Ways to [try to] slow the Solar Century''
Archives
Jan Galkowski
Category Archives: probabilistic programming
Cory Lesmeister’s treatment of Simson’s Paradox (at “Fear and Loathing in Data Science”)
(Updated 2016-05-08, to provide reference for plateaus of ML functions in vicinity of MLE.) Simpson’s Paradox is one of those phenomena of data which really give Statistics a substance and a role, beyond the roles it inherits from, say, theoretical … Continue reading
Posted in Akaike Information Criterion, approximate Bayesian computation, Bayes, Bayesian, evidence, Frequentist, games of chance, information theoretic statistics, Kalman filter, likelihood-free, mathematics, maths, maximum likelihood, Monte Carlo Statistical Methods, probabilistic programming, rationality, Rauch-Tung-Striebel, Simpson's Paradox, state-space models, statistical dependence, statistics, stochastics
Leave a comment
“Grid shading by simulated annealing” [Martyn Plummer]
Source: Grid shading by simulated annealing (or what I did on my holidays), aka “fun with GCHQ job adverts”, by Martyn Plummer, developer of JAGS. Excerpt: I wanted to solve the puzzle but did not want to sit down with … Continue reading
Posted in approximate Bayesian computation, Bayesian, Bayesian inversion, Boltzmann, BUGS, Christian Robert, Gibbs Sampling, JAGS, likelihood-free, Markov Chain Monte Carlo, Martyn Plummer, mathematics, maths, MCMC, Monte Carlo Statistical Methods, optimization, probabilistic programming, SPSA, stochastic algorithms, stochastic search
Leave a comment
Generating supports for classification rules in black box regression models
Inspired by the extensive and excellent work in approximate Bayesian computation (see also), especially that done by Professors Christian Robert and colleagues (see also), and Professor Simon Wood (see also), it occurred to me that the complaints regarding lack of … Continue reading
Posted in approximate Bayesian computation, Bayes, Bayesian, Bayesian inversion, generalized linear models, machine learning, numerical analysis, numerical software, probabilistic programming, rationality, reasonableness, state-space models, statistics, stochastic algorithms, stochastic search, stochastics, support of black boxes
Leave a comment
What the future of energy everywhere looks like
What will the energy landscape look like after utility companies are either dead, dying, or revert to a tiny portion of their territory? Silicon Valley CCE Partnership gives us all a clue. It’s been described in the San Francisco Chronicle, … Continue reading
Posted in adaptation, Anthropocene, capricious gods, chance, citizenship, civilization, clean disruption, conservation, consumption, decentralized electric power generation, decentralized energy, demand-side solutions, destructive economic development, dynamical systems, economics, efficiency, energy, energy reduction, energy utilities, engineering, environment, ethics, forecasting, fossil fuel divestment, geophysics, global warming, Hyper Anthropocene, investment in wind and solar energy, living shorelines, mesh models, meteorology, microgrids, mitigation, obfuscating data, oceanography, physical materialism, physics, pipelines, planning, politics, prediction, probabilistic programming, public utility commissions, PUCs, quantum, reasonableness, reproducible research, risk, Sankey diagram, science, sea level rise, selfishness, solar energy, solar power, SolarPV.tv, Spaceship Earth, statistics, stochastic algorithms, stochastics, Svante Arrhenius, taxes, temporal myopia, the right to know, the value of financial assets, transparency, UU Humanists, WHOI, wind energy, wind power, zero carbon
Leave a comment
Solar array with cloud predicting technology launched in WA
Australia’s first grid-connected solar power project with cloud predicting technology launched at Karratha Airport, WA, in bid to smooth solar supply. Source: Solar array with cloud predicting technology launched in WA
Posted in adaptation, Anthropocene, carbon dioxide, citizenship, civilization, clean disruption, climate, climate change, climate disruption, conservation, consumption, decentralized electric power generation, decentralized energy, demand-side solutions, dynamic linear models, efficiency, energy, energy reduction, energy utilities, engineering, environment, ethics, forecasting, geophysics, global warming, Hyper Anthropocene, investment in wind and solar energy, Kalman filter, mathematics, maths, meteorology, microgrids, mitigation, NCAR, numerical software, optimization, physics, prediction, probabilistic programming, rationality, reasonableness, risk, science, solar power, stochastics, sustainability, time series
Leave a comment
Thank You
And thanks, Tamino!
Posted in astrophysics, citizen science, climate change, climate data, climate disruption, climate education, climate models, differential equations, dynamical systems, ecology, ensembles, forecasting, games of chance, geophysics, global warming, hiatus, Hyper Anthropocene, IPCC, mathematics, mathematics education, maths, meteorology, model comparison, new forms of scientific peer review, open data, open source scientific software, physics, probabilistic programming, probability, rationality, reasonableness, reproducible research, risk, science, science education, spatial statistics, statistics, Tamino, the right to know, time series, transparency
Leave a comment
“Cauchy Distribution: Evil or Angel?” (from Xian)
Cauchy Distribution: Evil or Angel?. From Professor Christian Robert.
“A vignette on Metropolis” (Christian Robert)
This is a very welcome addition by a master of Bayesian computation, providing a great, brief answer for many of my colleagues who ask, “What’s this MCMC thing about anyway?”
“Unbiased Bayes for Big Data: Path of partial posteriors” (Christian Robert)
Unbiased Bayes for Big Data: Path of partial posteriors.
Christian Robert on the amazing Gibbs sampler
Professor Christian Robert remarks on the amazing Gibbs sampler. Implicitly he’s also underscoring the power of properly done Bayesian computational analysis. For here we have a problem with a posterior distribution having two strong modes, so a point estimate, like … Continue reading
The designers of our climate
The blog … And Then There’s Physics wades deeply into the recent Monckton-Soon-Legates-Briggs paper. And, they conclude, what it is saying is that, conditional upon no feedbacks, equilibrium climate sensitivity (“ECS”) needs to be small. Except that they don’t say … Continue reading
Posted in astrophysics, bridge to nowhere, carbon dioxide, carbon dioxide capture, carbon dioxide sequestration, Carbon Tax, Carl Sagan, citizenship, civilization, climate, climate change, climate education, differential equations, ecology, economics, engineering, environment, ethics, forecasting, fossil fuel divestment, geoengineering, geophysics, humanism, IPCC, mathematics, mathematics education, maths, meteorology, methane, NASA, NCAR, Neill deGrasse Tyson, NOAA, oceanography, open data, open source scientific software, physics, politics, population biology, Principles of Planetary Climate, probabilistic programming, R, rationality, reasonableness, reproducible research, risk, science, science education, scientific publishing, sociology, solar power, statistics, testing, the right to know
1 Comment
Heads-up limit hold’em poker is solved
This is from today’s news in Science. The full citation is: M. Bowling, N. Burch, M. Johanson, O. Tammelin, “Heads-up limit hold’em poker is solved”, Science, 9 January 2015, 347(6218), 145-149, http://dx.doi.org/10.1126/science.1259433. See also a University of Alberta site where … Continue reading
Posted in games of chance, probabilistic programming, risk
Leave a comment
On nested equivalence classes of climate models, ordered by computational complexity
I’m digging into the internals of ABC, for professional and scientific reasons. I’ve linked a great tutorial elsewhere, and argued that this framework, advanced by Wood, and Wilkinson (Robert), and Wilkinson (Darren), and Hartig and colleagues, and Robert and colleagues, … Continue reading
Posted in approximate Bayesian computation, Bayes, Bayesian, biology, ecology, environment, forecasting, geophysics, IPCC, mathematics, maths, MCMC, meteorology, NCAR, NOAA, oceanography, optimization, population biology, Principles of Planetary Climate, probabilistic programming, R, science, stochastic algorithms, stochastic search
Leave a comment
“[W]e want to model the process as we would simulate it.”
Professor Darren Wilkinson offers a pithy insight on how to go about constructing statistical models, notably hierarchical ones: “… we want to model the process as we would simulate it ….” This appears in his blog post One-way ANOVA with … Continue reading
Posted in approximate Bayesian computation, Bayes, Bayesian, biology, ecology, engineering, forecasting, mathematics, mathematics education, maths, model comparison, optimization, population biology, probabilistic programming, rationality, reasonableness, risk, science, science education, sociology, statistics, stochastic algorithms
Tagged ANOVA
Leave a comment
struggling with problems already partly solved by others
Climate modelers and models see as their frontier the problem of dealing with spontaneous dynamics in systems such as atmosphere or ocean which are not directly forced by boundary conditions such as radiative forcing due to increased greenhouse gas (“GHG”) … Continue reading
Posted in approximate Bayesian computation, Bayes, Bayesian, biology, climate, climate education, differential equations, ecology, engineering, environment, geophysics, IPCC, mathematics, mathematics education, meteorology, model comparison, NCAR, NOAA, oceanography, physics, population biology, probabilistic programming, rationality, reasonableness, risk, science, science education, statistics, stochastic algorithms, stochastic search
1 Comment
illustrating particle filters and Bayesian fusion using successive location estimates on the unit circle
Introduction Modern treatments of Bayesian integration to obtain posterior densities often use some form of Markov Chain Monte Carlo (“MCMC”), typically Gibbs sampling. Gibbs works well with many Bayesian hierarchical models. The standard problem-solving situation with these is that a … Continue reading
An equation-free introduction to Bayesian inference
By Tomoharu Eguchi from 2008: “An Introduction to Bayesian Statistics Without Using Equations“.
example of Bayesian inversion
This is based upon my solution of Exercise 2.3, page 18, R. Christensen, W. Johnson, A. Branscum, T. E. Hanson, Bayesian Ideas and Data Analysis, Chapman & Hall, 2011. The purpose is to show how information latent in a set … Continue reading
Bayesian deconvolution of stick lengths
Consider trying to determine the length of a straight stick. Instead of the measurement errors being clustered about zero, suppose the errors are known to be always positive, that is, no measurement ever underestimates the length of the stick. Such … Continue reading
Blind Bayesian recovery of components of residential solid waste tonnage from totals data
This is a sketch of how maths and statistics can do something called blind source separation, meaning to estimate the components of data given only their totals. Here, I use Bayesian techniques for the purpose, sometimes called Bayesian inversion, using … Continue reading
“The joy and martyrdom of trying to be a Bayesian”
Bayesians have all been there. Some of us don’t depend upon producing publications to assure our pay, so we less have the pressure of pleasing peer reviewers. Nonetheless, it’s all reacting to “What the hell are you doing? I don’t … Continue reading
How fast is JAGS?
How fast is JAGS?.
Comment on “How urban anonymity disappears when all data is tracked”, an article in the NY Times
The New York Times has an article titled “How urban anonymity disappears when all data is tracked” by Quentin Hardy which appears in its “Bits” section. I just posted a comment on that article, which is reproduced below: I hope … Continue reading
“The most common fallacy in discussing extreme weather events”: Stefan Rahmstorf
The most common fallacy in discussing extreme weather events.
Dr David Gallo of WHOI on today’s “Face the Nation” on CBS: MH370
Good to see Dr Dave Gallo speaking about WHOI’s approach to AF447 and its similarity to MH370. Update. 2014-03-26. WHOI is getting ready to deploy their REMUS 6000 systems. Update. 2014-03-28. The Woods Hole Oceanographic Institution has offered its expertise … Continue reading
Posted in engineering, history, meteorology, oceanography, probabilistic programming, WHOI
Tagged AF447, MH370
Leave a comment
The zero-crossings trick for JAGS: Finding roots stochastically
BUGS has a “zeros trick” (Lund, Jackson, Best, Thomas, Spiegelhalter, 2013, pages 204-206; see also an online illustration) for specifying a new distribution which is not in the standard set. The idea is to couple an invented-for-the-moment Poisson density to … Continue reading
Posted in Bayesian, BUGS, education, forecasting, Gibbs Sampling, JAGS, mathematics, MCMC, probabilistic programming, R, statistics, stochastic search
Tagged error-in-variables problem, optimization, zeros trick
4 Comments
“Data-driven science is a failure of imagination” (Petr Keil)
Happened across this today … I could not agree more: “Data-driven science is a failure of imagination” by Petr Keil. I look forward to reading his posts on Bayesian statistics.
Posted in Bayesian, engineering, history, mathematics, maths, MCMC, probabilistic programming, rationality, science
Tagged data mining, data science
Leave a comment
ecoquant
