### Distributed Solar: The Democratizaton of Energy

### Blogroll

- Risk and Well-Being
- 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
- Los Alamos Center for Bayesian Methods
- Earle Wilson
- Subsidies for wind and solar versus subsidies for fossil fuels
- Ives and Dakos techniques for regime changes in series
- The Plastic Pick-Up: Discovering new sources of marine plastic pollution
- Mertonian norms
- Peter Congdon's Bayesian statistical modeling Peter Congdon’s collection of links pertaining to his several books on Bayesian modeling
- ggplot2 and ggfortify Plotting State Space Time Series with ggplot2 and ggfortify
- Harvard's Project Implicit
- SASB Sustainability Accounting Standards Board
- 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/.
- 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.
- "Consider a Flat Pond" Invited talk introducing systems thinking, by Jan Galkowski, at First Parish in Needham, UU, via Zoom
- Leverhulme Centre for Climate Change Mitigation
- Leadership lessons from Lao Tzu
- South Shore Recycling Cooperative Materials management, technical assistance and networking, town advocacy, public outreach
- James' Empty Blog
- Slice Sampling
- Flettner Rotor Bruce Yeany introduces the Flettner Rotor and related science
- Dominic Cummings blog Chief advisor to the PM, United Kingdom
- American Statistical Association
- "Perpetual Ocean" from NASA GSFC
- Hermann Scheer Hermann Scheer was a visionary, a major guy, who thought deep thoughts about energy, and its implications for humanity’s relationship with physical reality
- 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.”
- Mrooijer's Numbers R 4Us
- Karl Broman
- 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/
- Beautiful Weeds of New York City
- Team Andrew Weinberg Walking September 8th for the Jimmy Fund!
- Number Cruncher Politics
- Survey Methodology, Prof Ron Fricker http://faculty.nps.edu/rdfricke/
- John Kruschke's "Dong Bayesian data analysis" blog Expanding and enhancing John’s book of same title (now in second edition!)
- WEAPONS OF MATH DESTRUCTION Cathy O’Neil’s WEAPONS OF MATH DESTRUCTION,
- Earth Family Alpha Michael Osborne’s blog (former Executive at Austin Energy, now Chairman of the Electric Utility Commission for Austin, Texas)
- Fear and Loathing in Data Science Cory Lesmeister’s savage journey to the heart of Big Data
- Earth Family Beta MIchael Osborne’s blog on Science and the like
- OOI Data Nuggets OOI Ocean Data Lab: The Data Nuggets
- John Cook's reasons to use Bayesian inference
- distributed solar and matching location to need
- Dr James Spall's SPSA
- Bob Altemeyer on authoritarianism (via Dan Satterfield) The science behind the GOP civil war
- WEAPONS OF MATH DESTRUCTION, reviews Reviews of Cathy O’Neil’s new book
- Charlie Kufs' "Stats With Cats" blog “You took Statistics 101. Now what?”
- All about models
- Nadler Strategy, LLC, on sustainability Thinking about business, efficient and effective management, and business value
- "The Expert"
- 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.
- 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.

### climate change

- James Hansen and granddaughter Sophie on moving forward with progress on climate
- Simple models of climate change
- Interview with Wally Broecker Interview with Wally Broecker
- 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
- 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.
- Warming slowdown discussion
- 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 Irrelevance of Saturation: Why Carbon Dioxide Matters'' (Bart Levenson)
- RealClimate
- Risk and Well-Being
- "A field guide to the climate clowns"
- "Getting to the Energy Future We Want," Dr Steven Chu
- 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.
- 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.
- 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
- Berkeley Earth Surface Temperature
- Ray Pierrehumbert's site related to "Principles of Planetary Climate" THE book on climate science
- The Green Plate Effect Eli Rabett’s “The Green Plate Effect”
- Tamino's Open Mind Open Mind: A statistical look at climate, its science, and at science denial
- Sea Change Boston
- Ice and Snow
- "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
- “Ways to [try to] slow the Solar Century''
- The net average effect of a warming climate is increased aridity (Professor Steven Sherwood)
- HotWhopper: It's excellent. Global warming and climate change. Eavesdropping on the deniosphere, its weird pseudo-science and crazy conspiracy whoppers.
- Eli on the spectroscopic basis of atmospheric radiation physical chemistry
- Dessler's 6 minute Greenhouse Effect video
- "Lessons of the Little Ice Age" (Farber) From Dan Farber, at LEGAL PLANET
- "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.
- "Betting strategies on fluctuations in the transient response of greenhouse warming" By Risbey, Lewandowsky, Hunter, Monselesan: Betting against climate change on durations of 15+ years is no longer a rational proposition.
- Mrooijer's Global Temperature Explorer
- "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.)
- 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%.
- Simple box models and climate forcing IMO one of Tamino’s best posts illustrating climate forcing using simple box models
- Rabett Run Incisive analysis of climate science versus deliberate distraction
- “The discovery of global warming'' (American Institute of Physics)
- Spectra Energy exposed
- Andy Zucker's "Climate Change and Psychology"
- Équiterre Equiterre helps build a social movement by encouraging individuals, organizations and governments to make ecological and equitable choices, in a spirit of solidarity.
- 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.
- Thriving on Low Carbon
- 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.
- `Who to believe on climate change': Simple checks By Bart Verheggen
- Jacobson WWS literature index
- Climate Change Reports By John and Mel Harte
- "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.
- 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
- Documenting the Climate Deniarati at work

### Archives

### Jan Galkowski

# Category Archives: MCMC

## 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
2 Comments

## Repaired R code for Markov spatial simulation of hurricane tracks from historical trajectories

(Slight update, 28th June 2020.) I’m currently studying random walk and diffusion processes and their connections with random fields. I’m interested in this because at the core of dynamic linear models, Kalman filters, and state-space methods there is a random … Continue reading

Posted in American Meteorological Association, American Statistical Association, AMETSOC, Arthur Charpentier, atmosphere, diffusion, diffusion processes, dynamic linear models, dynamical systems, environment, geophysics, hurricanes, Kalman filter, Kerry Emanuel, Lévy flights, Lorenz, Markov chain random fields, mathematics, mathematics education, maths, MCMC, mesh models, meteorological models, meteorology, model-free forecasting, Monte Carlo Statistical Methods, numerical analysis, numerical software, oceanography, open data, open source scientific software, physics, random walk processes, random walks, science, spatial statistics, state-space models, statistical dependence, statistics, stochastic algorithms, stochastics, time series
1 Comment

## Newt Gingrich and Van Jones. Right on.

It’s the thing. And it addresses how media and people forget about the actual statistics, and focus on the White Hot Bright Light. A study by Gelman, Fagan, and Kiss A study by Freyer A counterpoint to the Freyer study … Continue reading

Posted in American Statistical Association, Bayes, Bayesian, citizen science, criminal justice, Daniel Kahneman, ethics, evidence, fear uncertainty and doubt, humanism, Lives Matter, logistic regression, Markov Chain Monte Carlo, MCMC, organizational failures, population biology, rationality, reasonableness, risk, statistics, Susan Jacoby, the right to know
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## On Smart Data

One of the things I find surprising, if not astonishing, is that in the rush to embrace Big Data, a lot of learning and statistical technique has been left apparently discarded along the way. I’m hardly the first to point … Continue reading

Posted in Akaike Information Criterion, Bayes, Bayesian, Bayesian inversion, big data, bigmemory package for R, changepoint detection, data science, data streams, dlm package, dynamic generalized linear models, dynamic linear models, dynamical systems, Generalize Additive Models, generalized linear models, information theoretic statistics, Kalman filter, linear algebra, logistic regression, machine learning, Markov Chain Monte Carlo, mathematics, mathematics education, maths, maximum likelihood, MCMC, Monte Carlo Statistical Methods, multivariate statistics, numerical analysis, numerical software, numerics, quantitative biology, quantitative ecology, rationality, reasonableness, sampling, smart data, state-space models, statistical dependence, statistics, the right to know, time series
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## p-values and hypothesis tests: the Bayesian(s) rule

The American Statistical Association of which I am a longtime member issued an important statement today which will hopefully move statistical practice in engineering and especially in the sciences away from the misleading practice of using p-values and hypothesis tests. … Continue reading

Posted in approximate Bayesian computation, arXiv, Bayes, Bayesian, Bayesian inversion, bollocks, Christian Robert, climate, complex systems, data science, Frequentist, information theoretic statistics, likelihood-free, Markov Chain Monte Carlo, MCMC, Monte Carlo Statistical Methods, population biology, rationality, reasonableness, science, scientific publishing, statistical dependence, statistics, stochastics, Student t distribution
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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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## R and “big data”

On 2nd November 2015, Wes McKinney, the developer of the highly useful Python pandas module (and other things, including books), wrote an amusing blog post, “The problem with the data science language wars“. I by no means disagree with him. … Continue reading

## Sea Surface Anomalies

(Hat tip to Susan Stone.) The graphic below shows sea surface temperature anomalies relative to the 1971-2000 baseline First data are courtesy of the Climate Reanalyzer, a joint project of the Climate Change Institute at the University of Maine, and … Continue reading

Posted in Anthropocene, carbon dioxide, climate, climate change, climate disruption, climate education, differential equations, diffusion processes, dynamical systems, ecology, ENSO, environment, forecasting, geophysics, global warming, Hyper Anthropocene, IPCC, mathematics, MCMC, NASA, NCAR, NOAA, oceanography, open data, physics, Principles of Planetary Climate, rationality, reasonableness, risk, science, science education, sea level rise, statistics, sustainability, the right to know, time series, transparency
1 Comment

## “… the most patronizing start to an answer I have ever received …”

Professor Christian Robert tries to help out a student of MCMC on Cross Validated and earns the comment that his help had “the most patronizing start to an answer I have ever received“. I learned a new term: primitivus petitor.

## “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…

## “Unbiased Bayes for Big Data: Path of partial posteriors” (Christian Robert)

Unbiased Bayes for Big Data: Path of partial posteriors.

## Markov Chain Monte Carlo methods and logistic regression

This post could also be subtitled “Residual deviance isn’t the whole story.” My favorite book on logistic regression is by Dr Joseph Hilbe, Logistic Regression Models, CRC Press, 2009, Chapman & Hill. It is a solidly frequentist text, but its … Continue reading

Posted in Bayes, Bayesian, logistic regression, MCMC, notes, R, statistics, stochastic algorithms, stochastic search
3 Comments

## Bayesian change-point analysis for global temperatures, 1850-2010

Professor Peter Congdon reports on two Bayesian models for global temperature shifts in his textbook, Applied Bayesian Modelling, as “Example 6.12: Global temperatures, 1850-2010”, on pages 252-253. A direct link is available online. The first is apparently original with Congdon, … Continue reading

## 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

## 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
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## Liddell and Kruschke, on conditional logistic Bayesian estimation

(“Ostracism and fines in a public goods game with accidental contributions: The importance of punishment type”) An overview. The article

Posted in Bayes, Bayesian, biology, citizenship, civilization, compassion, ecology, economics, ethics, humanism, investing, MCMC, politics, rationality, reasonableness, risk, sociology, statistics
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## 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

## 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?.

## Sea Level Rise, after Church and White (2006)

Modeling done with a Bayesian Rauch-Tung-Striebel algorithm, estimating priors of variance for observations and state by using a stationary bootstrap for the series using Politis and Romano algorithm. Updated, 30th September 2021 Zhu, Yingli, Gary T. Mitchum, Kara S. Doran, … Continue reading

Posted in Bayesian, carbon dioxide, civilization, climate, climate education, conservation, consumption, ecology, economics, education, efficiency, energy, energy reduction, engineering, environment, forecasting, geoengineering, geophysics, humanism, MCMC, meteorology, oceanography, optimization, physics, politics, rationality, reasonableness, science, statistics
3 Comments

## Bayes vs the virial theorem

Bayes vs the virial theorem.

Posted in Bayesian, mathematics, maths, MCMC, reasonableness, science, statistics
4 Comments

## 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
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