Distributed Solar: The Democratizaton of Energy
Blogroll
- 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
- Team Andrew Weinberg Walking September 8th for the Jimmy Fund!
- Harvard's Project Implicit
- 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.
- Professor David Draper
- Brian McGill's Dynamic Ecology blog Quantitative biology with pithy insights regarding applications of statistical methods
- WEAPONS OF MATH DESTRUCTION, reviews Reviews of Cathy O’Neil’s new book
- 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.
- 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.”
- What If
- Charlie Kufs' "Stats With Cats" blog “You took Statistics 101. Now what?”
- 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/
- Survey Methodology, Prof Ron Fricker http://faculty.nps.edu/rdfricke/
- distributed solar and matching location to need
- "Talking Politics" podcast David Runciman, Helen Thompson
- Gabriel's staircase
- Nadler Strategy, LLC, on sustainability Thinking about business, efficient and effective management, and business value
- SASB Sustainability Accounting Standards Board
- "Perpetual Ocean" from NASA GSFC
- American Statistical Association
- 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/.
- Carl Safina's blog One of the wisest on Earth
- South Shore Recycling Cooperative Materials management, technical assistance and networking, town advocacy, public outreach
- 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/
- 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
- Leadership lessons from Lao Tzu
- Lenny Smith's CHAOS: A VERY SHORT INTRODUCTION This is a PDF version of Lenny Smith’s book of the same title, also available from Amazon.com
- John Kruschke's "Dong Bayesian data analysis" blog Expanding and enhancing John’s book of same title (now in second edition!)
- Brendon Brewer on Overfitting Important and insightful presentation by Brendon Brewer on overfitting
- Los Alamos Center for Bayesian Methods
- 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.
- ggplot2 and ggfortify Plotting State Space Time Series with ggplot2 and ggfortify
- Risk and Well-Being
- Slice Sampling
- Dr James Spall's SPSA
- Fear and Loathing in Data Science Cory Lesmeister’s savage journey to the heart of Big Data
- James' Empty Blog
- American Association for the Advancement of Science (AAAS)
- Ted Dunning
- Label Noise
- All about models
- Comprehensive Guide to Bayes Rule
- Mark Berliner's video lecture "Bayesian mechanistic-statistical modeling with examples in geophysical settings"
- Karl Broman
- Mrooijer's Numbers R 4Us
- Peter Congdon's Bayesian statistical modeling Peter Congdon’s collection of links pertaining to his several books on Bayesian modeling
- The Keeling Curve: its history History of the Keeling Curve and Charles David Keeling
- Healthy Home Healthy Planet
- Quotes by Nikola Tesla Quotes by Nikola Tesla, including some of others he greatly liked.
- Earth Family Alpha Michael Osborne’s blog (former Executive at Austin Energy, now Chairman of the Electric Utility Commission for Austin, Texas)
climate change
- Bloomberg interactive graph on “What's warming the world''
- Ellenbogen: There is no Such Thing as Wind Turbine Syndrome
- Updating the Climate Science: What path is the real world following? From Professors Makiko Sato & James Hansen of Columbia University
- "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
- James Powell on sampling the climate consensus
- Transitioning to fully renewable energy Professor Saul Griffiths talks to transitioning the customer journey, from a dependency upon fossil fuels to an electrified future
- 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.
- "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.
- Wally Broecker on climate realism
- Earth System Models
- David Appell's early climate science
- 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.
- SOLAR PRODUCTION at Westwood Statistical Studios Generation charts for our home in Westwood, MA
- Grid parity map for Solar PV in United States
- Jacobson WWS literature index
- Anti—Anti-#ClimateEmergency Whether to declare a climate emergency is debatable. But some critics have gone way overboard.
- Climate at a glance Current state of the climate, from NOAA
- Thriving on Low Carbon
- Ricky Rood's “What would happen to climate if we (suddenly) stopped emitting GHGs today?
- HotWhopper: It's excellent. Global warming and climate change. Eavesdropping on the deniosphere, its weird pseudo-science and crazy conspiracy whoppers.
- Rabett Run Incisive analysis of climate science versus deliberate distraction
- The Scientific Case for Modern Human-caused Global Warming
- World Weather Attribution
- Skeptical Science
- Klaus Lackner (ASU), Silicon Kingdom Holdings (SKH) Capturing CO2 from air at scale
- Energy payback period for solar panels Considering everything, how long do solar panels have to operate to offset the energy used to produce them?
- "Lessons of the Little Ice Age" (Farber) From Dan Farber, at LEGAL PLANET
- 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
- Tuft's Professor Kenneth Lang on the physical chemistry of the Greenhouse Effect
- The Carbon Cycle The Carbon Cycle, monitored by The Carbon Project
- Sir David King David King’s perspective on climate, and the next thousands of years for humanity
- MIT's Climate Primer
- `Who to believe on climate change': Simple checks By Bart Verheggen
- “The discovery of global warming'' (American Institute of Physics)
- Ray Pierrehumbert's site related to "Principles of Planetary Climate" THE book on climate science
- 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
- Andy Zucker's "Climate Change and Psychology"
- Climate Change Denying Organizations
- Solar Gardens Community Power
- 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.
- Professor Robert Strom's compendium of resources on climate change Truly excellent
- Interview with Wally Broecker Interview with Wally Broecker
- Climate Change Reports By John and Mel Harte
- “The Irrelevance of Saturation: Why Carbon Dioxide Matters'' (Bart Levenson)
- Spectra Energy exposed
- Sea Change Boston
- The Sunlight Economy
- The net average effect of a warming climate is increased aridity (Professor Steven Sherwood)
- “Ways to [try to] slow the Solar Century''
- "A field guide to the climate clowns"
Archives
Jan Galkowski
Category Archives: information theoretic statistics
Complexity vs Simplicity in Geophysics
Really interesting mechanistic reductionism illustrating what it means to explain phenomena scientifically. It’s all about the maths.
Posted in abstraction, American Association for the Advancement of Science, American Meteorological Association, American Statistical Association, Azimuth Project, complex systems, control theory, differential equations, dynamical systems, eigenanalysis, information theoretic statistics, mathematics, Mathematics and Climate Research Network, mechanistic models, nonlinear systems, Paul Pukite, spectra, spectral methods, spectroscopy, theoretical physics, wave equations, WHT
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Procrustes tangent distance is better than SNCD
I’ve written two posts here on using a Symmetrized Normalized Compression Divergence or SNCD for comparing time series. One introduced the SNCD and described its relationship to compression distance, and the other applied the SNCD to clustering days at a … Continue reading
Posted in data science, dependent data, descriptive statistics, divergence measures, hydrology, Ian Dryden, information theoretic statistics, J.T.Kent, Kanti Mardia, non-parametric statistics, normalized compression divergence, quantitative ecology, R statistical programming language, spatial statistics, statistical series, time series
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A look at an electricity consumption series using SNCDs for clustering
(Slightly amended with code and data link, 12th January 2019.) Prediction of electrical load demand or, in other words, electrical energy consumption is important for the proper operation of electrical grids, at all scales. RTOs and ISOs forecast demand based … Continue reading
Posted in American Statistical Association, consumption, data streams, decentralized electric power generation, dendrogram, divergence measures, efficiency, electricity, electricity markets, energy efficiency, energy utilities, ensembles, evidence, forecasting, grid defection, hierarchical clustering, hydrology, ILSR, information theoretic statistics, local self reliance, Massachusetts, microgrids, NCD, normalized compression divergence, numerical software, open data, prediction, rate of return regulation, Sankey diagram, SNCD, statistical dependence, statistical series, statistics, sustainability, symmetric normalized compression divergence, time series
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Series, symmetrized Normalized Compressed Divergences and their logit transforms
(Major update on 11th January 2019. Minor update on 16th January 2019.) On comparing things The idea of a calculating a distance between series for various purposes has received scholarly attention for quite some time. The most common application is … Continue reading
Posted in Akaike Information Criterion, bridge to somewhere, computation, content-free inference, data science, descriptive statistics, divergence measures, engineering, George Sughihara, information theoretic statistics, likelihood-free, machine learning, mathematics, model comparison, model-free forecasting, multivariate statistics, non-mechanistic modeling, non-parametric statistics, numerical algorithms, statistics, theoretical physics, thermodynamics, time series
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The Johnson-Lindenstrauss Lemma, and the paradoxical power of random linear operators. Part 1.
Updated, 2018-12-04 I’ll be discussing the ramifications of: William B. Johnson and Joram Lindenstrauss, “Extensions of Lipschitz mappings into a Hilbert space, Contemporary Mathematics, 26:189–206, 1984. for several posts here. Some introduction and links to proofs and explications will be … Continue reading
Posted in clustering, data science, dimension reduction, information theoretic statistics, Johnson-Lindenstrauss Lemma, k-NN, Locality Sensitive Hashing, mathematics, maths, multivariate statistics, non-parametric model, numerical algorithms, numerical linear algebra, point pattern analysis, random projections, recommender systems, science, stochastic algorithms, stochastics, subspace projection methods
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Why smooth?
I’ve encountered a number of blog posts this week which seem not to understand the Bias-Variance Tradeoff in regard to Mean-Squared-Error. These arose in connection with smoothing splines, which I was studying in connection with multivariate adaptive regression splines, that … Continue reading
Posted in Akaike Information Criterion, American Statistical Association, Antarctica, carbon dioxide, climate change, denial, global warming, information theoretic statistics, likelihood-free, multivariate adaptive regression splines, non-parametric model, science denier, smoothing, splines, statistical dependence
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Polls, Political Forecasting, and the Plight of Five Thirty Eight
On 17th October 2016 AT 7:30 p.m., Nate Silver of FiveThirtyEight.com wrote about how, as former Secretary of State Hillary Clinton’s polling numbers got better, it was more difficult for FiveThirtyEight‘s models to justify increasing her probability of winning, although … Continue reading
Posted in abstraction, American Statistical Association, anemic data, citizen science, citizenship, civilization, economics, education, forecasting, information theoretic statistics, mathematics, maths, politics, prediction markets, sociology, the right to know, theoretical physics, thermodynamics
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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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Six cases of models
The previous post included an attempt to explain land surface temperatures as estimated by the BEST project using a dynamic linear model including regressions on both quarterly CO2 concentrations and ocean heat content. The idea was to check the explanatory … Continue reading
Posted in AMETSOC, anemic data, Anthropocene, astrophysics, Bayesian, Berkeley Earth Surface Temperature project, BEST, carbon dioxide, climate, climate change, climate data, climate disruption, climate models, dlm package, dynamic linear models, dynamical systems, environment, fossil fuels, geophysics, Giovanni Petris, global warming, greenhouse gases, Hyper Anthropocene, information theoretic statistics, maths, maximum likelihood, meteorology, model comparison, numerical software, Patrizia Campagnoli, Rauch-Tung-Striebel, Sonia Petrone, state-space models, stochastic algorithms, stochastic search, SVD, time series
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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
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Gavin Simpson updates his temperature analysis
See the very interesting discussion at his blog, From the bottom of the heap. It would be nice to see some information theoretic measures on these results, though.
Posted in AMETSOC, Anthropocene, astrophysics, Berkeley Earth Surface Temperature project, carbon dioxide, changepoint detection, climate, climate change, climate data, climate disruption, climate models, ecology, environment, evidence, Gavin Simpson, Generalize Additive Models, geophysics, global warming, HadCRUT4, hiatus, Hyper Anthropocene, information theoretic statistics, Kalman filter, maths, meteorology, numerical analysis, R, rationality, reasonableness, splines, time series
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HadCRUT4 and GISTEMP series filtered and estimated with simple RTS model
Happy Vernal Equinox! This post has been updated today with some of the equations which correspond to the models. An assessment of whether or not there was a meaningful slowdown or “hiatus” in global warming, was recently discussed by Tamino … Continue reading
Posted in AMETSOC, anemic data, Bayesian, boosting, bridge to somewhere, cat1, changepoint detection, climate, climate change, climate data, climate disruption, climate models, complex systems, computation, data science, dynamical systems, geophysics, George Sughihara, global warming, hiatus, information theoretic statistics, machine learning, maths, meteorology, MIchael Mann, multivariate statistics, physics, prediction, Principles of Planetary Climate, rationality, reasonableness, regime shifts, sea level rise, 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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dynamic linear model applied to sea-level-rise anomalies
I spent much of the data working up a function for level+trend dynamic linear modeling based upon the dlm package by Petris, Petrone, and Campagnoli, while trying some calculations and code for regime shift detection. One of the test cases … Continue reading
Posted in Bayesian, citizen science, climate change, climate data, climate disruption, dynamic linear models, floods, forecasting, Frequentist, global warming, icesheets, information theoretic statistics, Kalman filter, meteorology, open data, sea level rise, state-space models, statistics, time series
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Southern New England Meteorology Conference, 24th October 2015
I attending the 2015 edition of the Southern New England Meteorology Conference in Milton, MA, near the Blue Hill, and its Blue Hill Climatological Observatory, of which I am a member as we as of the American Meteorological Society. I … Continue reading
Posted in Anthropocene, capricious gods, climate, Dan Satterfield, dynamical systems, ensembles, ENSO, environment, floods, forecasting, geophysics, Hyper Anthropocene, information theoretic statistics, mesh models, meteorology, model comparison, NCAR, NOAA, nor'easters, oceanography, probability, science, spatial statistics, state-space models, statistics, stochastic algorithms, stochastic search, stochastics, time series
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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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“Cauchy Distribution: Evil or Angel?” (from Xian)
Cauchy Distribution: Evil or Angel?. From Professor Christian Robert.
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
engineering and understanding with stable models
Stable distributions or Lévy -stable models is a class of probability distributions which contains the Gaussian, the Cauchy (or Lorentz), and the Lévy distribution. They are parameterized by an which is . Values of of 1 or less give distributions … Continue reading
Posted in approximate Bayesian computation, Bayesian, citizen science, climate, climate change, climate education, differential equations, diffusion processes, ecology, economics, forecasting, geophysics, information theoretic statistics, IPCC, mathematics, mathematics education, maths, meteorology, model comparison, NOAA, oceanography, physics, rationality, reasonableness, risk, science, science education, stochastic search, the right to know
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“… making a big assumption …”
“That’s making a big assumption.” (This post is a follow-on from an earlier one.) In the colloquial, the phrase means basing an argument on a precondition which is unusual or atypical or offends common sense. When applied to scientific hypotheses, … Continue reading
ecoquant
