Distributed Solar: The Democratizaton of Energy
Blogroll
- distributed solar and matching location to need
- American Association for the Advancement of Science (AAAS)
- Dr James Spall's SPSA
- Team Andrew Weinberg Walking September 8th for the Jimmy Fund!
- James' Empty Blog
- Mertonian norms
- London Review of Books
- The Alliance for Securing Democracy dashboard
- WEAPONS OF MATH DESTRUCTION Cathy O’Neil’s WEAPONS OF MATH DESTRUCTION,
- GeoEnergy Math Prof Paul Pukite’s Web site devoted to energy derived from geological and geophysical processes and categorized according to its originating source.
- OOI Data Nuggets OOI Ocean Data Lab: The Data Nuggets
- Tony Seba Solar energy, electric vehicle, energy storage, and business disruption professor and visionary
- Mrooijer's Numbers R 4Us
- What If
- 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
- AP Statistics: Sampling, by Michael Porinchak Twin City Schools
- Carl Safina's blog One of the wisest on Earth
- Comprehensive Guide to Bayes Rule
- Dollars per BBL: Energy in Transition
- Earth Family Beta MIchael Osborne’s blog on Science and the like
- Brendon Brewer on Overfitting Important and insightful presentation by Brendon Brewer on overfitting
- American Statistical Association
- Brian McGill's Dynamic Ecology blog Quantitative biology with pithy insights regarding applications of statistical methods
- Subsidies for wind and solar versus subsidies for fossil fuels
- 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.
- Beautiful Weeds of New York City
- Quotes by Nikola Tesla Quotes by Nikola Tesla, including some of others he greatly liked.
- NCAR AtmosNews
- Nadler Strategy, LLC, on sustainability Thinking about business, efficient and effective management, and business value
- Los Alamos Center for Bayesian Methods
- Giant vertical monopolies for energy have stopped making sense
- The Mermaid's Tale A conversation about biological complexity and evolution, and the societal aspects of science
- 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/.
- Bob Altemeyer on authoritarianism (via Dan Satterfield) The science behind the GOP civil war
- 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.
- Dominic Cummings blog Chief advisor to the PM, United Kingdom
- The Keeling Curve: its history History of the Keeling Curve and Charles David Keeling
- Ted Dunning
- 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”
- 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
- Healthy Home Healthy Planet
- 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.
- Slice Sampling
- All about Sankey diagrams
- Professor David Draper
- Risk and Well-Being
- Gabriel's staircase
- John Kruschke's "Dong Bayesian data analysis" blog Expanding and enhancing John’s book of same title (now in second edition!)
- Darren Wilkinson's introduction to ABC Darren Wilkinson’s introduction to approximate Bayesian computation (“ABC”). See also his post about summary statistics for ABC https://darrenjw.wordpress.com/2013/09/01/summary-stats-for-abc/
climate change
- James Hansen and granddaughter Sophie on moving forward with progress on climate
- Ice and Snow
- Documenting the Climate Deniarati at work
- Professor Robert Strom's compendium of resources on climate change Truly excellent
- Updating the Climate Science: What path is the real world following? From Professors Makiko Sato & James Hansen of Columbia University
- The HUMAN-caused greenhouse effect, in under 5 minutes, by Bill Nye
- 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
- Ellenbogen: There is no Such Thing as Wind Turbine Syndrome
- "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.
- World Weather Attribution
- SOLAR PRODUCTION at Westwood Statistical Studios Generation charts for our home in Westwood, MA
- Tell Utilities Solar Won't Be Killed Barry Goldwater, Jr’s campaign to push for solar expansion against monopolistic utilities, as a Republican
- James Powell on sampling the climate consensus
- Wally Broecker on climate realism
- 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.
- Risk and Well-Being
- "Mighty Microgrids" Webinar This is a Webinar on YouTube about Microgrids from the Institute for Local Self-Reliance (ILSR), featuring New York State and Minnesota
- Climate Change Denying Organizations
- The Sunlight Economy
- 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.
- Tamino's Open Mind Open Mind: A statistical look at climate, its science, and at science denial
- Grid parity map for Solar PV in United States
- MIT's Climate Primer
- Climate at a glance Current state of the climate, from NOAA
- RealClimate
- 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
- The Scientific Case for Modern Human-caused Global Warming
- Model state level energy policy for New Englad Bob Massie’s proposed energy policy for Massachusetts, an admirable model for energy policy anywhere in New England
- Skeptical Science
- Thriving on Low Carbon
- The Green Plate Effect Eli Rabett’s “The Green Plate Effect”
- “The Irrelevance of Saturation: Why Carbon Dioxide Matters'' (Bart Levenson)
- Dessler's 6 minute Greenhouse Effect video
- Climate Change: A health emergency … New England Journal of Medicine Caren G. Solomon, M.D., M.P.H., and Regina C. LaRocque, M.D., M.P.H., January 17, 2019 N Engl J Med 2019; 380:209-211 DOI: 10.1056/NEJMp1817067
- 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.
- Agendaists Eli Rabett’s coining of a phrase
- History of discovering Global Warming From the American Institute of Physics.
- Transitioning to fully renewable energy Professor Saul Griffiths talks to transitioning the customer journey, from a dependency upon fossil fuels to an electrified future
- Jacobson WWS literature index
- Simple box models and climate forcing IMO one of Tamino’s best posts illustrating climate forcing using simple box models
- Energy payback period for solar panels Considering everything, how long do solar panels have to operate to offset the energy used to produce them?
- The net average effect of a warming climate is increased aridity (Professor Steven Sherwood)
- Warming slowdown discussion
- Eli on the spectroscopic basis of atmospheric radiation physical chemistry
- Exxon-Mobil statement on UNFCCC COP21
- "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.
- Climate Communication Hassol, Somerville, Melillo, and Hussin site communicating climate to the public
- Andy Zucker's "Climate Change and Psychology"
- `Who to believe on climate change': Simple checks By Bart Verheggen
- Sea Change Boston
Archives
Jan Galkowski
Category Archives: Gibbs Sampling
Reanalysis of business visits from deployments of a mobile phone app
Updated, 20th October 2020 This reports a reanalysis of data from the deployment of a mobile phone app, as reported in: M. Yauck, L.-P. Rivest, G. Rothman, “Capture-recapture methods for data on the activation of applications on mobile phones“, Journal … Continue reading
Posted in Bayesian computational methods, biology, capture-mark-recapture, capture-recapture, Christian Robert, count data regression, cumulants, diffusion, diffusion processes, Ecological Society of America, ecology, epidemiology, experimental science, field research, Gibbs Sampling, Internet measurement, Jean-Michel Marin, linear regression, mark-recapture, mathematics, maximum likelihood, Monte Carlo Statistical Methods, multilist methods, multivariate statistics, non-mechanistic modeling, non-parametric statistics, numerics, open source scientific software, Pierre-Simon Laplace, population biology, population dynamics, quantitative biology, quantitative ecology, R, R statistical programming language, sampling, sampling algorithms, segmented package in R, statistical ecology, statistical models, statistical regression, statistical series, statistics, stepwise approximation, stochastic algorithms, surveys, V. M. R. Muggeo
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Sampling: Rejection, Reservoir, and Slice
An article by Suilou Huang for catatrophe modeler AIR-WorldWide of Boston about rejection sampling in CAT modeling got me thinking about pulling together some notes about sampling algorithms of various kinds. There are, of course, books written about this subject, … Continue reading
Posted in accept-reject methods, American Statistical Association, Bayesian computational methods, catastrophe modeling, data science, diffusion processes, empirical likelihood, Gibbs Sampling, insurance, Markov Chain Monte Carlo, mathematics, Mathematics and Climate Research Network, maths, Monte Carlo Statistical Methods, multivariate statistics, numerical algorithms, numerical analysis, numerical software, numerics, percolation theory, Python 3 programming language, R statistical programming language, Radford Neal, sampling, slice sampling, spatial statistics, statistics, stochastic algorithms, stochastic search
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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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high dimension Metropolis-Hastings algorithms
If attempting to simulate from a multivariate standard normal distribution in a large dimension, when starting from the mode of the target, i.e., its mean γ, leaving the mode γis extremely unlikely, given the huge drop between the value of the density at the mode γ and at likely realisations Continue reading
Posted in Bayes, Bayesian, Bayesian inversion, boosting, chance, Christian Robert, computation, ensembles, Gibbs Sampling, James Spall, Jerome Friedman, Markov Chain Monte Carlo, mathematics, maths, MCMC, Monte Carlo Statistical Methods, multivariate statistics, numerical software, numerics, optimization, reasonableness, Robert Schapire, SPSA, state-space models, statistics, stochastic algorithms, stochastic search, stochastics, Yoav Freund
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“The Bayesian Second Law of Thermodynamics” (Sean Carroll, and collaborators)
http://www.preposterousuniverse.com/blog/2015/08/11/the-bayesian-second-law-of-thermodynamics/ See also.
Posted in approximate Bayesian computation, Bayesian, bifurcations, Boltzmann, capricious gods, dynamical systems, ensembles, games of chance, Gibbs Sampling, information theoretic statistics, Josiah Willard Gibbs, mathematics, maths, physics, probability, rationality, reasonableness, science, statistics, stochastic algorithms, stochastics, thermodynamics, Wordpress
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“A vignette on Metropolis” (Christian Robert)
Originally posted on Xi'an's Og:
Over the past week, I wrote a short introduction to the Metropolis-Hastings algorithm, mostly in the style of our Introduction to Monte Carlo with R book, that is, with very little theory and…
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
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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HadCRUT4 version “HadCRUT.4.2.0.0” available as .RData R workspace or image
I’m happy to announce that I have made available the HadCRUT4 observational ensemble data as an .RData image for use with R. These were downloaded from the MetOffice Hadley Observations Web site. Detailed documentation is available on this page, with the … Continue reading
ecoquant
667 per centimeter : climate science, quantitative biology, statistics, and energy policy 