### Distributed Solar: The Democratizaton of Energy

### Blogroll

- James' Empty Blog
- distributed solar and matching location to need
- Patagonia founder Yvon Chouinard on how businesses can help our collective environmental mess Patagonia’s Yvon Chouinard set the standard for how a business can mitigate the ravages of capitalism on earth’s environment. At 81 years old, he’s just getting started.
- Survey Methodology, Prof Ron Fricker http://faculty.nps.edu/rdfricke/
- The Plastic Pick-Up: Discovering new sources of marine plastic pollution
- "Consider a Flat Pond" Invited talk introducing systems thinking, by Jan Galkowski, at First Parish in Needham, UU, via Zoom
- Quotes by Nikola Tesla Quotes by Nikola Tesla, including some of others he greatly liked.
- 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”
- London Review of Books
- Gabriel's staircase
- Team Andrew Weinberg Walking September 8th for the Jimmy Fund!
- 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.”
- Earle Wilson
- Rasmus Bååth's Research Blog Bayesian statistics and data analysis
- Thaddeus Stevens quotes As I get older, I admire this guy more and more
- The Alliance for Securing Democracy dashboard
- 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/
- Peter Congdon's Bayesian statistical modeling Peter Congdon’s collection of links pertaining to his several books on Bayesian modeling
- Harvard's Project Implicit
- 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.
- Awkward Botany
- Beautiful Weeds of New York City
- Nadler Strategy, LLC, on sustainability Thinking about business, efficient and effective management, and business value
- American Statistical Association
- Leverhulme Centre for Climate Change Mitigation
- Flettner Rotor Bruce Yeany introduces the Flettner Rotor and related science
- All about Sankey diagrams
- WEAPONS OF MATH DESTRUCTION Cathy O’Neil’s WEAPONS OF MATH DESTRUCTION,
- AP Statistics: Sampling, by Michael Porinchak Twin City Schools
- Dr James Spall's SPSA
- Mark Berliner's video lecture "Bayesian mechanistic-statistical modeling with examples in geophysical settings"
- Los Alamos Center for Bayesian Methods
- "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.
- 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.
- Woods Hole Oceanographic Institution (WHOI)
- Comprehensive Guide to Bayes Rule
- Brian McGill's Dynamic Ecology blog Quantitative biology with pithy insights regarding applications of statistical methods
- International Society for Bayesian Analysis (ISBA)
- Charlie Kufs' "Stats With Cats" blog “You took Statistics 101. Now what?”
- Bob Altemeyer on authoritarianism (via Dan Satterfield) The science behind the GOP civil war
- Mrooijer's Numbers R 4Us
- Slice Sampling
- 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.
- Dollars per BBL: Energy in Transition
- Carl Safina's blog One of the wisest on Earth
- Professor David Draper
- Karl Broman
- "Perpetual Ocean" from NASA GSFC
- ggplot2 and ggfortify Plotting State Space Time Series with ggplot2 and ggfortify
- Risk and Well-Being

### climate change

- Energy payback period for solar panels Considering everything, how long do solar panels have to operate to offset the energy used to produce them?
- History of discovering Global Warming From the American Institute of Physics.
- `Who to believe on climate change': Simple checks By Bart Verheggen
- 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
- The Scientific Case for Modern Human-caused Global Warming
- David Appell's early climate science
- The Carbon Cycle The Carbon Cycle, monitored by The Carbon Project
- Eli on the spectroscopic basis of atmospheric radiation physical chemistry
- Anti—Anti-#ClimateEmergency Whether to declare a climate emergency is debatable. But some critics have gone way overboard.
- The Sunlight Economy
- Simple box models and climate forcing IMO one of Tamino’s best posts illustrating climate forcing using simple box models
- "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
- 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.
- Équiterre Equiterre helps build a social movement by encouraging individuals, organizations and governments to make ecological and equitable choices, in a spirit of solidarity.
- "Lessons of the Little Ice Age" (Farber) From Dan Farber, at LEGAL PLANET
- Mathematics and Climate Research Network The Mathematics and Climate Research Network (MCRN) engages mathematicians to collaborating on the cryosphere, conceptual model validation, data assimilation, the electric grid, food systems, nonsmooth systems, paleoclimate, resilience, tipping points.
- Reanalyses.org
- “The Irrelevance of Saturation: Why Carbon Dioxide Matters'' (Bart Levenson)
- Interview with Wally Broecker Interview with Wally Broecker
- Transitioning to fully renewable energy Professor Saul Griffiths talks to transitioning the customer journey, from a dependency upon fossil fuels to an electrified future
- Professor Robert Strom's compendium of resources on climate change Truly excellent
- US$165/tonne CO2: Sweden Sweden has a Carbon Dioxide tax of US$165 per tonne at present. CO2 tax was imposed in 1991. GDP has grown 60%.
- The net average effect of a warming climate is increased aridity (Professor Steven Sherwood)
- Warming slowdown discussion
- weather blocking patterns
- HotWhopper: It's excellent. Global warming and climate change. Eavesdropping on the deniosphere, its weird pseudo-science and crazy conspiracy whoppers.
- Wally Broecker on climate realism
- 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
- Risk and Well-Being
- 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.
- Simple models of climate change
- World Weather Attribution
- Agendaists Eli Rabett’s coining of a phrase
- ATTP summarizes all that stuff about Committed Warming from AND THEN THERE’S PHYSICS
- The HUMAN-caused greenhouse effect, in under 5 minutes, by Bill Nye
- Solar Gardens Community Power
- Updating the Climate Science: What path is the real world following? From Professors Makiko Sato & James Hansen of Columbia University
- Mrooijer's Global Temperature Explorer
- "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.
- Earth System Models
- Tuft's Professor Kenneth Lang on the physical chemistry of the Greenhouse Effect
- Ellenbogen: There is no Such Thing as Wind Turbine Syndrome
- "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.
- Wind sled Wind sled: A zero carbon way of exploring ice sheets
- 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
- Climate Change Denying Organizations
- “Ways to [try to] slow the Solar Century''
- 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.
- Jacobson WWS literature index
- "Getting to the Energy Future We Want," Dr Steven Chu

### 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
1 Comment

## 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