Distributed Solar: The Democratizaton of Energy
Blogroll
- Professor David Draper
- What If
- WEAPONS OF MATH DESTRUCTION, reviews Reviews of Cathy O’Neil’s new book
- Musings on Quantitative Paleoecology Quantitative methods and palaeoenvironments.
- Ted Dunning
- Leadership lessons from Lao Tzu
- Peter Congdon's Bayesian statistical modeling Peter Congdon’s collection of links pertaining to his several books on Bayesian modeling
- John Cook's reasons to use Bayesian inference
- Dollars per BBL: Energy in Transition
- Flettner Rotor Bruce Yeany introduces the Flettner Rotor and related science
- Leverhulme Centre for Climate Change Mitigation
- Charlie Kufs' "Stats With Cats" blog “You took Statistics 101. Now what?”
- Thaddeus Stevens quotes As I get older, I admire this guy more and more
- 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.
- 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.
- SASB Sustainability Accounting Standards Board
- Awkward Botany
- 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.
- BioPython A collection of Python tools for quantitative Biology
- 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.
- Ives and Dakos techniques for regime changes in series
- AP Statistics: Sampling, by Michael Porinchak Twin City Schools
- Mertonian norms
- The Keeling Curve: its history History of the Keeling Curve and Charles David Keeling
- International Society for Bayesian Analysis (ISBA)
- Busting Myths About Heat Pumps Heat pumps are perhaps the most efficient heating and cooling systems available. Recent literature distributed by utilities hawking natural gas and other sources use performance figures from heat pumps as they were available 15 years ago. See today’s.
- 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.”
- Brian McGill's Dynamic Ecology blog Quantitative biology with pithy insights regarding applications of statistical methods
- Gabriel's staircase
- Karl Broman
- OOI Data Nuggets OOI Ocean Data Lab: The Data Nuggets
- Nadler Strategy, LLC, on sustainability Thinking about business, efficient and effective management, and business value
- 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
- Quotes by Nikola Tesla Quotes by Nikola Tesla, including some of others he greatly liked.
- American Statistical Association
- Harvard's Project Implicit
- "Consider a Flat Pond" Invited talk introducing systems thinking, by Jan Galkowski, at First Parish in Needham, UU, via Zoom
- Earth Family Alpha Michael Osborne’s blog (former Executive at Austin Energy, now Chairman of the Electric Utility Commission for Austin, Texas)
- 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/
- "Talking Politics" podcast David Runciman, Helen Thompson
- Los Alamos Center for Bayesian Methods
- Woods Hole Oceanographic Institution (WHOI)
- All about Sankey diagrams
- GeoEnergy Math Prof Paul Pukite’s Web site devoted to energy derived from geological and geophysical processes and categorized according to its originating source.
- Comprehensive Guide to Bayes Rule
- John Kruschke's "Dong Bayesian data analysis" blog Expanding and enhancing John’s book of same title (now in second edition!)
- Dr James Spall's SPSA
- American Association for the Advancement of Science (AAAS)
- Subsidies for wind and solar versus subsidies for fossil fuels
climate change
- Berkeley Earth Surface Temperature
- Agendaists Eli Rabett’s coining of a phrase
- 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.
- RealClimate
- Climate Change Denying Organizations
- Simple box models and climate forcing IMO one of Tamino’s best posts illustrating climate forcing using simple box models
- Grid parity map for Solar PV in United States
- ATTP summarizes all that stuff about Committed Warming from AND THEN THERE’S PHYSICS
- Earth System Models
- Sea Change Boston
- Eli on the spectroscopic basis of atmospheric radiation physical chemistry
- Energy payback period for solar panels Considering everything, how long do solar panels have to operate to offset the energy used to produce them?
- Ellenbogen: There is no Such Thing as Wind Turbine Syndrome
- David Appell's early climate science
- All Models Are Wrong Dr Tamsin Edwards blog about uncertainty in science, and climate science
- 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%.
- SOLAR PRODUCTION at Westwood Statistical Studios Generation charts for our home in Westwood, MA
- "Climate science is setttled enough"
- `The unchained goddess' 1958 Bell Telephone Science Hour broadcast regarding, among other things, climate change.
- 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.
- The Scientific Case for Modern Human-caused Global Warming
- Klaus Lackner (ASU), Silicon Kingdom Holdings (SKH) Capturing CO2 from air at scale
- Warming slowdown discussion
- 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
- "Lessons of the Little Ice Age" (Farber) From Dan Farber, at LEGAL PLANET
- Wind sled Wind sled: A zero carbon way of exploring ice sheets
- Interview with Wally Broecker Interview with Wally Broecker
- The Carbon Cycle The Carbon Cycle, monitored by The Carbon Project
- Updating the Climate Science: What path is the real world following? From Professors Makiko Sato & James Hansen of Columbia University
- And Then There's Physics
- James Hansen and granddaughter Sophie on moving forward with progress on climate
- 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.
- 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.
- 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.
- Reanalyses.org
- The HUMAN-caused greenhouse effect, in under 5 minutes, by Bill Nye
- 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
- Thriving on Low Carbon
- History of discovering Global Warming From the American Institute of Physics.
- Équiterre Equiterre helps build a social movement by encouraging individuals, organizations and governments to make ecological and equitable choices, in a spirit of solidarity.
- Climate impacts on retail and supply chains
- “Ways to [try to] slow the Solar Century''
- Solar Gardens Community Power
- Climate at a glance Current state of the climate, from NOAA
- "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.
- Non-linear feedbacks in climate (discussion of Bloch-Johnson, Pierrehumbert, Abbot paper) Discussion of http://onlinelibrary.wiley.com/wol1/doi/10.1002/2015GL064240/abstract
- Social Cost of Carbon
- "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.
- `Who to believe on climate change': Simple checks By Bart Verheggen
- Bloomberg interactive graph on “What's warming the world''
Archives
Jan Galkowski
Category Archives: Durbin and Koopman
Phase Plane plots of COVID-19 deaths with uncertainties
I. Introduction. It’s time to fulfill the promise made in “Phase plane plots of COVID-19 deaths“, a blog post from 2nd May 2020, and produce the same with uncertainty clouds about the functional trajectories(*). To begin, here are some assumptions … Continue reading
Posted in American Statistical Association, Andrew Harvey, anomaly detection, count data regression, COVID-19, dependent data, dlm package, Durbin and Koopman, dynamic linear models, epidemiology, filtering, forecasting, Kalman filter, LaTeX, model-free forecasting, Monte Carlo Statistical Methods, numerical algorithms, numerical linear algebra, population biology, population dynamics, prediction, R, R statistical programming language, regression, statistical learning, stochastic algorithms
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