Distributed Solar: The Democratizaton of Energy
Blogroll
- Peter Congdon's Bayesian statistical modeling Peter Congdon’s collection of links pertaining to his several books on Bayesian modeling
- International Society for Bayesian Analysis (ISBA)
- Brian McGill's Dynamic Ecology blog Quantitative biology with pithy insights regarding applications of statistical methods
- SASB Sustainability Accounting Standards Board
- 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
- "Consider a Flat Pond" Invited talk introducing systems thinking, by Jan Galkowski, at First Parish in Needham, UU, via Zoom
- The Alliance for Securing Democracy dashboard
- 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.
- What If
- Dr James Spall's SPSA
- 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.
- Ives and Dakos techniques for regime changes in series
- The Keeling Curve: its history History of the Keeling Curve and Charles David Keeling
- Beautiful Weeds of New York City
- Tony Seba Solar energy, electric vehicle, energy storage, and business disruption professor and visionary
- Karl Broman
- 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.
- OOI Data Nuggets OOI Ocean Data Lab: The Data Nuggets
- Rasmus Bååth's Research Blog Bayesian statistics and data analysis
- Quotes by Nikola Tesla Quotes by Nikola Tesla, including some of others he greatly liked.
- Nadler Strategy, LLC, on sustainability Thinking about business, efficient and effective management, and business value
- Giant vertical monopolies for energy have stopped making sense
- Dollars per BBL: Energy in Transition
- Comprehensive Guide to Bayes Rule
- London Review of Books
- Team Andrew Weinberg Walking September 8th for the Jimmy Fund!
- 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
- Brendon Brewer on Overfitting Important and insightful presentation by Brendon Brewer on overfitting
- 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.”
- The Mermaid's Tale A conversation about biological complexity and evolution, and the societal aspects of science
- Survey Methodology, Prof Ron Fricker http://faculty.nps.edu/rdfricke/
- Mark Berliner's video lecture "Bayesian mechanistic-statistical modeling with examples in geophysical settings"
- Los Alamos Center for Bayesian Methods
- 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
- Risk and Well-Being
- 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
- Leverhulme Centre for Climate Change Mitigation
- Earle Wilson
- Mrooijer's Numbers R 4Us
- 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”
- 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/
- 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
- 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/.
- American Association for the Advancement of Science (AAAS)
- "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.
- Dominic Cummings blog Chief advisor to the PM, United Kingdom
- Woods Hole Oceanographic Institution (WHOI)
- Bob Altemeyer on authoritarianism (via Dan Satterfield) The science behind the GOP civil war
climate change
- "Climate science is setttled enough"
- “The Irrelevance of Saturation: Why Carbon Dioxide Matters'' (Bart Levenson)
- 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
- SolarLove
- Mrooijer's Global Temperature Explorer
- Transitioning to fully renewable energy Professor Saul Griffiths talks to transitioning the customer journey, from a dependency upon fossil fuels to an electrified future
- James Powell on sampling the climate consensus
- Wally Broecker on climate realism
- 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.
- The Carbon Cycle The Carbon Cycle, monitored by The Carbon Project
- Simple models of climate change
- 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.
- Sea Change Boston
- Solar Gardens Community Power
- Berkeley Earth Surface Temperature
- Wind sled Wind sled: A zero carbon way of exploring ice sheets
- ATTP summarizes all that stuff about Committed Warming from AND THEN THERE’S PHYSICS
- Jacobson WWS literature index
- Ice and Snow
- 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.
- Non-linear feedbacks in climate (discussion of Bloch-Johnson, Pierrehumbert, Abbot paper) Discussion of http://onlinelibrary.wiley.com/wol1/doi/10.1002/2015GL064240/abstract
- Skeptical Science
- All Models Are Wrong Dr Tamsin Edwards blog about uncertainty in science, and climate science
- RealClimate
- Ellenbogen: There is no Such Thing as Wind Turbine Syndrome
- The Scientific Case for Modern Human-caused Global Warming
- "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
- Ricky Rood's “What would happen to climate if we (suddenly) stopped emitting GHGs today?
- 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
- 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 discovery of global warming'' (American Institute of Physics)
- "Getting to the Energy Future We Want," Dr Steven Chu
- Nick Bower's "Scared Scientists"
- Thriving on Low Carbon
- weather blocking patterns
- 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.
- Bloomberg interactive graph on “What's warming the world''
- Klaus Lackner (ASU), Silicon Kingdom Holdings (SKH) Capturing CO2 from air at scale
- World Weather Attribution
- Professor Robert Strom's compendium of resources on climate change Truly excellent
- "Lessons of the Little Ice Age" (Farber) From Dan Farber, at LEGAL PLANET
- "A field guide to the climate clowns"
- Climate Change Denying Organizations
- An open letter to Steve Levitt
- Climate at a glance Current state of the climate, from NOAA
- "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.
- On Thomas Edison and Solar Electric Power
- SOLAR PRODUCTION at Westwood Statistical Studios Generation charts for our home in Westwood, MA
- Climate Communication Hassol, Somerville, Melillo, and Hussin site communicating climate to the public
- Exxon-Mobil statement on UNFCCC COP21
Archives
Jan Galkowski
Category Archives: Bayes
Oldie and Goodie: `Testing a point Null Hypothesis: The irreconcilability of p-values and evidence’
A blog post by Professor Christian Robert mentioned a paper by Professors James Berger and Tom Sellke, which I downloaded several years back but never got around to reading. J. O. Berger, T. M. Sellke, “Testing a point Null Hypothesis: … Continue reading
Posted in American Statistical Association, Bayes, Bayesian, p-value
Leave a comment
cdetools package for R: Dalmasso, et al [updated]
Just hit the “arXiv streets”: N. Dalmasso, T. Pospisil, A. B. Lee, R. Izbicki, P. E. Freeman, A. I. Malz, “Conditional Density Estimation Tools in Python and R with applications to photometric redshifts and likelihood-free cosmological inference”, arXiv.org > astro-ph … Continue reading
perceptions of likelihood
That’s from this Github repository, maintained by Zoni Nation, having this description. The original data are from a study by Sherman Kent at the U.S. CIA, and is quoted in at least once outside source discussing the problem. In addition … Continue reading
Merry Newtonmas tomorrow! On finding the area of the Batman Shape using Monte Carlo integration
It’s Newtonmas 2017 tomorrow! What better way to celebrate than talk about integration! The Batman Shape (sometimes called the Batman Curve, somewhat erroneously, I think) looks like this: You can find details about it at Wolfram MathWorld, including its area … Continue reading
Posted in Bayes, Calculus, Markov Chain Monte Carlo
Tagged Batman Curve, Batman Shape, James Schloss, Monte Carlo integration, slice sampling
1 Comment
David Spiegelhalter on `how to spot a dodgy statistic’
In this political season, it’s useful to brush up on rhetorical skills, particularly ones involving numbers and statistics, or what John Allen Paulos called numeracy. Professor David Spiegelhalter has written a guide to some of these tricks. Read the whole … Continue reading
Posted in abstraction, anemic data, Bayes, Bayesian, chance, citizenship, civilization, corruption, Daniel Kahneman, disingenuity, Donald Trump, education, games of chance, ignorance, maths, moral leadership, obfuscating data, open data, perceptions, politics, rationality, reason, reasonableness, rhetoric, risk, sampling, science, sociology, statistics, the right to know
Leave a 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
Leave a comment
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
Leave a comment
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
“Lucky d20” (by Tamino, with my reblogging comments)
Originally posted on Open Mind:
What with talk of killer heat waves, droughts, floods, etc. etc., this blog tends to get pretty serious. When it does, we don’t deal with happy prospects, but with the danger of worldwide catastrophe. But…
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
Leave a comment
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
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
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
On differential localization of tumors using relative concentrations of ctDNA. Part 2.
Part 1 of this series introduced the idea of ctDNA and its use for detecting cancers or their resurgence, and proposed a scheme whereby relative concentrations of ctDNA at two or more sites after controlled disturbance might be used to … Continue reading
Deep Recurrent Learning Networks
(Also known to statisticians as deep exponential families.) Large scale deep learning Four easy lessons on Deep Learning from Google
Posted in Bayes, Bayesian, neural networks, optimization
Leave a comment
Comprehensive and compact tutorial on Petris’ DLM package in R; with an update about Helske’s KFAS
A blogger named Lalas produced on Quantitative Thoughts a very comprehensive and compact tutorial on the R package dlm by Petris. I use dlm a lot. Unfortunately, Lalas does not give details on how the SVD is used. They do … Continue reading
Posted in Bayes, Bayesian, dynamic linear models, dynamical systems, forecasting, Kalman filter, mathematics, maths, multivariate statistics, numerical software, open source scientific software, prediction, R, Rauch-Tung-Striebel, state-space models, statistics, stochastic algorithms, SVD, time series
1 Comment
“Cauchy Distribution: Evil or Angel?” (from Xian)
Cauchy Distribution: Evil or Angel?. From Professor Christian Robert.
“… 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
“Big Data is the new Phrenology”
From mathbabe: Big Data is the new phrenology. Excerpt: Here’s the thing. What we’ve got is a new kind of awful pseudo-science, which replaces measurements of skulls with big data. There’s no reason to think this stuff is any less … Continue reading
Posted in anemic data, Bayes, Bayesian, bridge to nowhere, mathematics, maths, rationality, reasonableness, statistics
Leave a comment
R vs Python: Practical Data Analysis
R vs Python: Practical Data Analysis (Nonlinear Regression).
Posted in Bayes, Bayesian, biology, climate change, ecology, environment, Python 3, R, statistics, Wordpress
Leave a comment
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
Christian Robert on Alan Turing
Alan Turing Institute. See Professor Robert’s earlier post on Turing, too.
Posted in Bayes, Bayesian, citizenship, education, ethics, history, humanism, mathematics, maths, politics, rationality, reasonableness, statistics, stochastic algorithms, stochastic search, the right to know, Wordpress
Tagged Alan Turing
Leave a comment
Richard Muller: “I Was Wrong On Global Warming, But It Didn’t Convince The ‘Sceptics'”
Update. 26th February 2015 This is not directly related to the BEST project described in the YouTube video above, but the Berkeley National Laboratory has experimentally linked increases in radiative forcing with increases in atmospheric concentrations of CO2 due to … Continue reading
Posted in astrophysics, Bayes, carbon dioxide, citizenship, civilization, climate, climate change, climate education, differential equations, ecology, environment, geoengineering, geophysics, IPCC, mathematics, maths, meteorology, model comparison, NASA, NCAR, NOAA, oceanography, physics, population biology, rationality, Ray Pierrehumbert, reasonableness, reproducible research, risk, science, science education, sea level rise, the right to know
Leave a comment
ecoquant
