Distributed Solar: The Democratizaton of Energy
Blogroll
- Healthy Home Healthy Planet
- 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/
- Flettner Rotor Bruce Yeany introduces the Flettner Rotor and related science
- All about Sankey diagrams
- Brendon Brewer on Overfitting Important and insightful presentation by Brendon Brewer on overfitting
- Dollars per BBL: Energy in Transition
- distributed solar and matching location to need
- American Association for the Advancement of Science (AAAS)
- Mertonian norms
- Slice Sampling
- Comprehensive Guide to Bayes Rule
- Harvard's Project Implicit
- 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/
- Professor David Draper
- Peter Congdon's Bayesian statistical modeling Peter Congdon’s collection of links pertaining to his several books on Bayesian modeling
- Team Andrew Weinberg Walking September 8th for the Jimmy Fund!
- "Consider a Flat Pond" Invited talk introducing systems thinking, by Jan Galkowski, at First Parish in Needham, UU, via Zoom
- 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
- Rasmus Bååth's Research Blog Bayesian statistics and data analysis
- Musings on Quantitative Paleoecology Quantitative methods and palaeoenvironments.
- Carl Safina's blog One of the wisest on Earth
- Charlie Kufs' "Stats With Cats" blog “You took Statistics 101. Now what?”
- SASB Sustainability Accounting Standards Board
- Beautiful Weeds of New York City
- 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
- The Keeling Curve: its history History of the Keeling Curve and Charles David Keeling
- WEAPONS OF MATH DESTRUCTION, reviews Reviews of Cathy O’Neil’s new book
- ggplot2 and ggfortify Plotting State Space Time Series with ggplot2 and ggfortify
- GeoEnergy Math Prof Paul Pukite’s Web site devoted to energy derived from geological and geophysical processes and categorized according to its originating source.
- Earth Family Alpha Michael Osborne’s blog (former Executive at Austin Energy, now Chairman of the Electric Utility Commission for Austin, Texas)
- The Mermaid's Tale A conversation about biological complexity and evolution, and the societal aspects of science
- WEAPONS OF MATH DESTRUCTION Cathy O’Neil’s WEAPONS OF MATH DESTRUCTION,
- International Society for Bayesian Analysis (ISBA)
- OOI Data Nuggets OOI Ocean Data Lab: The Data Nuggets
- NCAR AtmosNews
- Subsidies for wind and solar versus subsidies for fossil fuels
- 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
- Karl Broman
- The Plastic Pick-Up: Discovering new sources of marine plastic pollution
- Gavin Simpson
- 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.”
- 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.
- Woods Hole Oceanographic Institution (WHOI)
- 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
- BioPython A collection of Python tools for quantitative Biology
- Tony Seba Solar energy, electric vehicle, energy storage, and business disruption professor and visionary
- The Alliance for Securing Democracy dashboard
- What If
- Dominic Cummings blog Chief advisor to the PM, United Kingdom
- 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.
climate change
- Risk and Well-Being
- Thriving on Low Carbon
- And Then There's Physics
- Grid parity map for Solar PV in United States
- 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.
- 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
- `Who to believe on climate change': Simple checks By Bart Verheggen
- MIT's Climate Primer
- The Sunlight Economy
- "A field guide to the climate clowns"
- "Getting to the Energy Future We Want," Dr Steven Chu
- Climate Communication Hassol, Somerville, Melillo, and Hussin site communicating climate to the public
- Sea Change Boston
- weather blocking patterns
- Climate impacts on retail and supply chains
- "Climate science is setttled enough"
- Tamino's Open Mind Open Mind: A statistical look at climate, its science, and at science denial
- Tell Utilities Solar Won't Be Killed Barry Goldwater, Jr’s campaign to push for solar expansion against monopolistic utilities, as a Republican
- Climate model projections versus observations
- The Green Plate Effect Eli Rabett’s “The Green Plate Effect”
- The Scientific Case for Modern Human-caused Global Warming
- Sir David King David King’s perspective on climate, and the next thousands of years for humanity
- Eli on the spectroscopic basis of atmospheric radiation physical chemistry
- 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.
- History of discovering Global Warming From the American Institute of Physics.
- "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
- "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
- Ellenbogen: There is no Such Thing as Wind Turbine Syndrome
- “The Irrelevance of Saturation: Why Carbon Dioxide Matters'' (Bart Levenson)
- Wind sled Wind sled: A zero carbon way of exploring ice sheets
- The Carbon Cycle The Carbon Cycle, monitored by The Carbon Project
- "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.
- Anti—Anti-#ClimateEmergency Whether to declare a climate emergency is debatable. But some critics have gone way overboard.
- `The unchained goddess' 1958 Bell Telephone Science Hour broadcast regarding, among other things, climate change.
- Updating the Climate Science: What path is the real world following? From Professors Makiko Sato & James Hansen of Columbia University
- Nick Bower's "Scared Scientists"
- SOLAR PRODUCTION at Westwood Statistical Studios Generation charts for our home in Westwood, MA
- HotWhopper: It's excellent. Global warming and climate change. Eavesdropping on the deniosphere, its weird pseudo-science and crazy conspiracy whoppers.
- Spectra Energy exposed
- ATTP summarizes all that stuff about Committed Warming from AND THEN THERE’S PHYSICS
- 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.
- On Thomas Edison and Solar Electric Power
- Bloomberg interactive graph on “What's warming the world''
- David Appell's early climate science
- 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.
- 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
- Professor Robert Strom's compendium of resources on climate change Truly excellent
- Earth System Models
- 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.
Archives
Jan Galkowski
Category Archives: dynamic generalized linear models
Calculating Derivatives from Random Forests
(Comment on prediction intervals for random forests, and links to a paper.) (Edits to repair smudges, 2020-06-28, about 0945 EDT. Closing comment, 2020-06-30, 1450 EDT.) There are lots of ways of learning about mathematical constructs, even about actual machines. One … Continue reading
Posted in bridge to somewhere, Calculus, dependent data, dynamic generalized linear models, dynamical systems, ensemble methods, ensemble models, filtering, forecasting, hierarchical clustering, linear regression, model-free forecasting, Monte Carlo Statistical Methods, non-mechanistic modeling, non-parametric model, non-parametric statistics, numerical algorithms, prediction, R statistical programming language, random forests, regression, sampling, splines, statistical learning, statistical series, statistics, time derivatives, time series
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A quick note on modeling operational risk from count data
The blog statcompute recently featured a proposal encouraging the use of ordinal models for difficult risk regressions involving count data. This is actually a second installment of a two-part post on this problem, the first dealing with flexibility in count … Continue reading
Posted in American Statistical Association, Bayesian, Bayesian computational methods, count data regression, dichotomising continuous variables, dynamic generalized linear models, Frank Harrell, Frequentist, Generalize Additive Models, generalized linear mixed models, generalized linear models, GLMMs, GLMs, John Kruschke, maximum likelihood, model comparison, Monte Carlo Statistical Methods, multivariate statistics, nonlinear, numerical software, numerics, premature categorization, probit regression, statistical regression, statistics
Tagged dichotomising continuous variables, dichotomizing continuous variables, premature categorization, splines
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on nonlinear dynamics of hordes of people
I spent a bit of last week at a symposium honoring the work of Charney and Lorenz in fluid dynamics. I am no serious student of fluid dynamics. I have a friend, Klaus, an engineer, who is, and makes a … Continue reading
Posted in Anthropocene, bifurcations, biology, Carl Safina, causation, complex systems, dynamic generalized linear models, dynamic linear models, dynamical systems, ecological services, ecology, Emily Shuckburgh, finance, Floris Takens, fluid dynamics, fluid eddies, games of chance, Hyper Anthropocene, investments, Lenny Smith, Lorenz, nonlinear, numerical algorithms, numerical analysis, politics, population biology, population dynamics, prediction markets, Principles of Planetary Climate, public transport, Ray Pierrehumbert, risk, sampling networks, sustainability, Timothy Lenton, Yale University Statistics Department, zero carbon, ``The tide is risin'/And so are we''
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Results of short literature search on impacts of climate change upon ecosystems and bird or animal migration patterns, from the journals of the Ecological Society of America
I decided to do a quick literature search on the impacts of climate change upon ecosystems and migration patterns. I could have kept the list private, but why not make it public? Not all these articles are purely about the … Continue reading
Posted in adaptation, American Statistical Association, Anthropocene, biology, climate change, climate education, climate models, complex systems, differential equations, dynamic generalized linear models, dynamical systems, ecological services, Ecological Society of America, ecology, Ecology Action, environment, evidence, global warming, Hyper Anthropocene, marine biology, mass extinctions, nonlinear systems, population biology, population dynamics, quantitative biology, quantitative ecology, tragedy of the horizon
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Chesterton’s fence, ecological sensitivity, and the disruption of ecological services
Hat tip to Matt Levine for introducing me to the term Chesteron’s fence: Chesterton’s fence is the principle that reforms should not be made until the reasoning behind the existing state of affairs is understood. … In the matter of … Continue reading
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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