### Distributed Solar: The Democratizaton of Energy

### Blogroll

- BioPython A collection of Python tools for quantitative Biology
- Ives and Dakos techniques for regime changes in series
- Slice Sampling
- SASB Sustainability Accounting Standards Board
- London Review of Books
- American Statistical Association
- What If
- Los Alamos Center for Bayesian Methods
- Subsidies for wind and solar versus subsidies for fossil fuels
- Tony Seba Solar energy, electric vehicle, energy storage, and business disruption professor and visionary
- ggplot2 and ggfortify Plotting State Space Time Series with ggplot2 and ggfortify
- Mrooijer's Numbers R 4Us
- Brian McGill's Dynamic Ecology blog Quantitative biology with pithy insights regarding applications of statistical methods
- "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.
- Peter Congdon's Bayesian statistical modeling Peter Congdon’s collection of links pertaining to his several books on Bayesian modeling
- "The Expert"
- Earth Family Beta MIchael Osborne’s blog on Science and the like
- Quotes by Nikola Tesla Quotes by Nikola Tesla, including some of others he greatly liked.
- 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
- Flettner Rotor Bruce Yeany introduces the Flettner Rotor and related science
- All about Sankey diagrams
- Fear and Loathing in Data Science Cory Lesmeister’s savage journey to the heart of Big Data
- Comprehensive Guide to Bayes Rule
- Dr James Spall's SPSA
- Gabriel's staircase
- 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/
- Bob Altemeyer on authoritarianism (via Dan Satterfield) The science behind the GOP civil war
- International Society for Bayesian Analysis (ISBA)
- Giant vertical monopolies for energy have stopped making sense
- 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.
- 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
- 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/
- The Alliance for Securing Democracy dashboard
- Carl Safina's blog One of the wisest on Earth
- Earth Family Alpha Michael Osborne’s blog (former Executive at Austin Energy, now Chairman of the Electric Utility Commission for Austin, Texas)
- Awkward Botany
- GeoEnergy Math Prof Paul Pukite’s Web site devoted to energy derived from geological and geophysical processes and categorized according to its originating source.
- All about models
- 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
- 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.
- Karl Broman
- American Association for the Advancement of Science (AAAS)
- Healthy Home Healthy Planet
- distributed solar and matching location to need
- AP Statistics: Sampling, by Michael Porinchak Twin City Schools
- The Mermaid's Tale A conversation about biological complexity and evolution, and the societal aspects of science
- 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/.
- John Cook's reasons to use Bayesian inference
- Risk and Well-Being

### climate change

- Reanalyses.org
- Tamino's Open Mind Open Mind: A statistical look at climate, its science, and at science denial
- Spectra Energy exposed
- Équiterre Equiterre helps build a social movement by encouraging individuals, organizations and governments to make ecological and equitable choices, in a spirit of solidarity.
- weather blocking patterns
- “Ways to [try to] slow the Solar Century''
- 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.
- Earth System Models
- Mrooijer's Global Temperature Explorer
- "Lessons of the Little Ice Age" (Farber) From Dan Farber, at LEGAL PLANET
- The HUMAN-caused greenhouse effect, in under 5 minutes, by Bill Nye
- 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
- Andy Zucker's "Climate Change and Psychology"
- HotWhopper: It's excellent. Global warming and climate change. Eavesdropping on the deniosphere, its weird pseudo-science and crazy conspiracy whoppers.
- Klaus Lackner (ASU), Silicon Kingdom Holdings (SKH) Capturing CO2 from air at scale
- Grid parity map for Solar PV in United States
- Exxon-Mobil statement on UNFCCC COP21
- "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.
- All Models Are Wrong Dr Tamsin Edwards blog about uncertainty in science, and climate science
- Jacobson WWS literature index
- "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
- 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.
- Ricky Rood's “What would happen to climate if we (suddenly) stopped emitting GHGs today?
- And Then There's Physics
- SOLAR PRODUCTION at Westwood Statistical Studios Generation charts for our home in Westwood, MA
- Risk and Well-Being
- Ray Pierrehumbert's site related to "Principles of Planetary Climate" THE book on climate science
- The Carbon Cycle The Carbon Cycle, monitored by The Carbon Project
- Ice and Snow
- Social Cost of Carbon
- 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.
- 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
- History of discovering Global Warming From the American Institute of Physics.
- 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
- Berkeley Earth Surface Temperature
- Tell Utilities Solar Won't Be Killed Barry Goldwater, Jr’s campaign to push for solar expansion against monopolistic utilities, as a Republican
- Agendaists Eli Rabett’s coining of a phrase
- 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
- The Sunlight Economy
- “The Irrelevance of Saturation: Why Carbon Dioxide Matters'' (Bart Levenson)
- Wally Broecker on climate realism
- "Getting to the Energy Future We Want," Dr Steven Chu
- Climate Change Reports By John and Mel Harte
- James Hansen and granddaughter Sophie on moving forward with progress on climate
- Eli on the spectroscopic basis of atmospheric radiation physical chemistry
- The net average effect of a warming climate is increased aridity (Professor Steven Sherwood)
- Tuft's Professor Kenneth Lang on the physical chemistry of the Greenhouse Effect
- Energy payback period for solar panels Considering everything, how long do solar panels have to operate to offset the energy used to produce them?
- Professor Robert Strom's compendium of resources on climate change Truly excellent

### Archives

### Jan Galkowski

# Category Archives: R statistical programming language

## 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
Tagged prediction intervals
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## 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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## Reanalysis of business visits from deployments of a mobile phone app

Updated, 20th October 2020 This reports a reanalysis of data from the deployment of a mobile phone app, as reported in: M. Yauck, L.-P. Rivest, G. Rothman, “Capture-recapture methods for data on the activation of applications on mobile phones“, Journal … Continue reading

Posted in Bayesian computational methods, biology, capture-mark-recapture, capture-recapture, Christian Robert, count data regression, cumulants, diffusion, diffusion processes, Ecological Society of America, ecology, epidemiology, experimental science, field research, Gibbs Sampling, Internet measurement, Jean-Michel Marin, linear regression, mark-recapture, mathematics, maximum likelihood, Monte Carlo Statistical Methods, multilist methods, multivariate statistics, non-mechanistic modeling, non-parametric statistics, numerics, open source scientific software, Pierre-Simon Laplace, population biology, population dynamics, quantitative biology, quantitative ecology, R, R statistical programming language, sampling, sampling algorithms, segmented package in R, statistical ecology, statistical models, statistical regression, statistical series, statistics, stepwise approximation, stochastic algorithms, surveys, V. M. R. Muggeo
1 Comment

## On odds of storms, and extreme precipitation

People talk about “thousand year storms”. Rather than being a storm having a recurrence time of once in a thousand years, these are storms which have a 0.001 chance per year of occurring. Storms aren’t the only weather events of … Continue reading

Posted in American Meteorological Association, American Statistical Association, AMETSOC, catastrophe modeling, climate disruption, climate economics, climate education, ecopragmatism, evidence, extreme events, extreme value distribution, flooding, floods, games of chance, global warming, global weirding, insurance, meteorological models, meteorology, R, R statistical programming language, real estate values, risk, Risky Business, riverine flooding, science, Significance
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## Macros in R

via Macros in R See also: The gtools package of R which enables these. There’s a description and motivation beginninng on page 11 of an (old: 2001) R News issue. They have been around a long time, but I haven’t … Continue reading

Posted in macros, R, R statistical programming language
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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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## On bag bans and sampling plans

Plastic bag bans are all the rage. It’s not the purpose of this post to take a position on the matter. Before you do, however, I’d recommend checking out this: and especially this: (Note: My lovely wife, Claire, presents this … Continue reading

Posted in bag bans, citizen data, citizen science, Commonwealth of Massachusetts, Ecology Action, evidence, Google, Google Earth, Google Maps, goverance, lifestyle changes, microplastics, municipal solid waste, oceans, open data, planning, plastics, politics, pollution, public health, quantitative ecology, R, R statistical programming language, reasonableness, recycling, rhetorical statistics, sampling, sampling networks, statistics, surveys, sustainability
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## Sampling: Rejection, Reservoir, and Slice

An article by Suilou Huang for catatrophe modeler AIR-WorldWide of Boston about rejection sampling in CAT modeling got me thinking about pulling together some notes about sampling algorithms of various kinds. There are, of course, books written about this subject, … Continue reading

Posted in accept-reject methods, American Statistical Association, Bayesian computational methods, catastrophe modeling, data science, diffusion processes, empirical likelihood, Gibbs Sampling, insurance, Markov Chain Monte Carlo, mathematics, Mathematics and Climate Research Network, maths, Monte Carlo Statistical Methods, multivariate statistics, numerical algorithms, numerical analysis, numerical software, numerics, percolation theory, Python 3 programming language, R statistical programming language, Radford Neal, sampling, slice sampling, spatial statistics, statistics, stochastic algorithms, stochastic search
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