Distributed Solar: The Democratizaton of Energy
Blogroll
- NCAR AtmosNews
- London Review of Books
- Mrooijer's Numbers R 4Us
- Los Alamos Center for Bayesian Methods
- The Mermaid's Tale A conversation about biological complexity and evolution, and the societal aspects of science
- 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.
- Rasmus Bååth's Research Blog Bayesian statistics and data analysis
- 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.
- "The Expert"
- Bob Altemeyer on authoritarianism (via Dan Satterfield) The science behind the GOP civil war
- Dominic Cummings blog Chief advisor to the PM, United Kingdom
- "Consider a Flat Pond" Invited talk introducing systems thinking, by Jan Galkowski, at First Parish in Needham, UU, via Zoom
- International Society for Bayesian Analysis (ISBA)
- John Cook's reasons to use Bayesian inference
- Musings on Quantitative Paleoecology Quantitative methods and palaeoenvironments.
- Prediction vs Forecasting: Knaub “Unfortunately, ‘prediction,’ such as used in model-based survey estimation, is a term that is often subsumed under the term ‘forecasting,’ but here we show why it is important not to confuse these two terms.”
- Charlie Kufs' "Stats With Cats" blog “You took Statistics 101. Now what?”
- Number Cruncher Politics
- South Shore Recycling Cooperative Materials management, technical assistance and networking, town advocacy, public outreach
- BioPython A collection of Python tools for quantitative Biology
- James' Empty Blog
- 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
- Tony Seba Solar energy, electric vehicle, energy storage, and business disruption professor and visionary
- 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
- American Association for the Advancement of Science (AAAS)
- Giant vertical monopolies for energy have stopped making sense
- GeoEnergy Math Prof Paul Pukite’s Web site devoted to energy derived from geological and geophysical processes and categorized according to its originating source.
- Earth Family Alpha Michael Osborne’s blog (former Executive at Austin Energy, now Chairman of the Electric Utility Commission for Austin, Texas)
- 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
- Earth Family Beta MIchael Osborne’s blog on Science and the like
- Team Andrew Weinberg Walking September 8th for the Jimmy Fund!
- Dollars per BBL: Energy in Transition
- SASB Sustainability Accounting Standards Board
- "Perpetual Ocean" from NASA GSFC
- All about models
- Flettner Rotor Bruce Yeany introduces the Flettner Rotor and related science
- Awkward Botany
- Mertonian norms
- Dr James Spall's SPSA
- WEAPONS OF MATH DESTRUCTION, reviews Reviews of Cathy O’Neil’s new book
- "Impacts of Green New Deal energy plans on grid stability, costs, jobs, health, and climate in 143 countries" (Jacobson, Delucchi, Cameron, et al) Global warming, air pollution, and energy insecurity are three of the greatest problems facing humanity. To address these problems, we develop Green New Deal energy roadmaps for 143 countries.
- Brendon Brewer on Overfitting Important and insightful presentation by Brendon Brewer on overfitting
- 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/
- Carl Safina's blog One of the wisest on Earth
- Quotes by Nikola Tesla Quotes by Nikola Tesla, including some of others he greatly liked.
- Karl Broman
- 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.
- Subsidies for wind and solar versus subsidies for fossil fuels
- Peter Congdon's Bayesian statistical modeling Peter Congdon’s collection of links pertaining to his several books on Bayesian modeling
- Label Noise
climate change
- Exxon-Mobil statement on UNFCCC COP21
- Mrooijer's Global Temperature Explorer
- Climate Change Reports By John and Mel Harte
- James Hansen and granddaughter Sophie on moving forward with progress on climate
- Reanalyses.org
- Social Cost of Carbon
- James Powell on sampling the climate consensus
- "Lessons of the Little Ice Age" (Farber) From Dan Farber, at LEGAL PLANET
- Jacobson WWS literature index
- 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
- Documenting the Climate Deniarati at work
- “Ways to [try to] slow the Solar Century''
- The net average effect of a warming climate is increased aridity (Professor Steven Sherwood)
- David Appell's early climate science
- Interview with Wally Broecker Interview with Wally Broecker
- Warming slowdown discussion
- Rabett Run Incisive analysis of climate science versus deliberate distraction
- 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.
- The Scientific Case for Modern Human-caused Global Warming
- Ricky Rood's “What would happen to climate if we (suddenly) stopped emitting GHGs today?
- `Who to believe on climate change': Simple checks By Bart Verheggen
- "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.
- AIP's history of global warming science: impacts The American Institute of Physics has a fine history of the science of climate change. This link summarizes the history of impacts of climate change.
- Climate Communication Hassol, Somerville, Melillo, and Hussin site communicating climate to the public
- NOAA Annual Greenhouse Gas Index report The annual assessment by the National Oceanic and Atmospheric Administration of the radiative forcing from constituent atmospheric greenhouse gases
- 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
- And Then There's Physics
- HotWhopper: It's excellent. Global warming and climate change. Eavesdropping on the deniosphere, its weird pseudo-science and crazy conspiracy whoppers.
- Updating the Climate Science: What path is the real world following? From Professors Makiko Sato & James Hansen of Columbia University
- CLIMATE ADAM Previously from the Science news staff at the podcast of Nature (“Nature Podcast”), the journal, now on YouTube, encouraging climate action through climate comedy.
- `The unchained goddess' 1958 Bell Telephone Science Hour broadcast regarding, among other things, climate change.
- Isaac Held's blog In the spirit of Ray Pierrehumbert’s “big ideas come from small models” in his textbook, PRINCIPLES OF PLANETARY CLIMATE, Dr Held presents quantitative essays regarding one feature or another of the Earth’s climate and weather system.
- "When Did Global Warming Stop" Doc Snow’s treatment of the denier claim that there’s been no warming for the most recent N years. (See http://hubpages.com/@doc-snow for more on him.)
- Sea Change Boston
- Thriving on Low Carbon
- Wally Broecker on climate realism
- RealClimate
- Anti—Anti-#ClimateEmergency Whether to declare a climate emergency is debatable. But some critics have gone way overboard.
- Ellenbogen: There is no Such Thing as Wind Turbine Syndrome
- "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.
- On Thomas Edison and Solar Electric Power
- Earth System Models
- Climate model projections versus observations
- Nick Bower's "Scared Scientists"
- Climate Change Denying Organizations
- Ray Pierrehumbert's site related to "Principles of Planetary Climate" THE book on climate science
- Risk and Well-Being
- Professor Robert Strom's compendium of resources on climate change Truly excellent
- 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.
- The HUMAN-caused greenhouse effect, in under 5 minutes, by Bill Nye
Archives
Jan Galkowski
Category Archives: JAGS
Less evidence for a global warming hiatus, and urging more use of Bayesian model averaging in climate science
(This post has been significantly updated midday 15th February 2018.) I’ve written about the supposed global warming hiatus of 2001-2014 before: “‘Overestimated global warming over the past 20 years’ (Fyfe, Gillett, Zwiers, 2013)”, 28 August 2013 “Warming Slowdown?”, Azimuth, Part … Continue reading
Posted in American Statistical Association, Andrew Parnell, anomaly detection, Anthropocene, Bayesian, Bayesian model averaging, Berkeley Earth Surface Temperature project, BEST, climate change, David Spiegelhalter, dependent data, Dublin, GISTEMP, global warming, Grant Foster, HadCRUT4, hiatus, Hyper Anthropocene, JAGS, Markov Chain Monte Carlo, Martyn Plummer, Mathematics and Climate Research Network, MCMC, model-free forecasting, Niamh Cahill, Significance, statistics, Stefan Rahmstorf, Tamino
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“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
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“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?”
We are trying. And the bitterest result is to have so-called colleagues align themselves with the Koch brothers
I attended a 350.org meeting tonight. One group A group presenting there called “Fighting Against Natural Gas” applauded themselves for assailing Senator Whitehouse of Rhode Island for his supportive position on natural gas pipelines. Now, I am no friend of … Continue reading
Posted in Anthropocene, astrophysics, Boston Ethical Society, bridge to nowhere, carbon dioxide, carbon dioxide sequestration, Carbon Tax, chemistry, citizenship, climate, climate change, climate education, consumption, decentralized electric power generation, demand-side solutions, ecology, economics, energy reduction, engineering, forecasting, fossil fuel divestment, investment in wind and solar energy, IPCC, JAGS, meteorology, methane, model comparison, NASA, natural gas, NCAR, Neill deGrasse Tyson, oceanography, open data, physics, politics, population biology, Principles of Planetary Climate, Python 3, R, rationality, reasonableness, reproducible research, risk, science, science education, Scripps Institution of Oceanography
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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
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
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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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?.
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
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ecoquant
