### Distributed Solar: The Democratizaton of Energy

### Blogroll

- Quotes by Nikola Tesla Quotes by Nikola Tesla, including some of others he greatly liked.
- Gavin Simpson
- International Society for Bayesian Analysis (ISBA)
- Professor David Draper
- 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
- Healthy Home Healthy Planet
- BioPython A collection of Python tools for quantitative Biology
- 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
- American Association for the Advancement of Science (AAAS)
- Thaddeus Stevens quotes As I get older, I admire this guy more and more
- Dominic Cummings blog Chief advisor to the PM, United Kingdom
- Karl Broman
- "Perpetual Ocean" from NASA GSFC
- Survey Methodology, Prof Ron Fricker http://faculty.nps.edu/rdfricke/
- Number Cruncher Politics
- Risk and Well-Being
- Rasmus Bååth's Research Blog Bayesian statistics and data analysis
- "Consider a Flat Pond" Invited talk introducing systems thinking, by Jan Galkowski, at First Parish in Needham, UU, via Zoom
- Ives and Dakos techniques for regime changes in series
- John Cook's reasons to use Bayesian inference
- 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
- Charlie Kufs' "Stats With Cats" blog “You took Statistics 101. Now what?”
- 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
- Mark Berliner's video lecture "Bayesian mechanistic-statistical modeling with examples in geophysical settings"
- 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/.
- Harvard's Project Implicit
- Earth Family Alpha Michael Osborne’s blog (former Executive at Austin Energy, now Chairman of the Electric Utility Commission for Austin, Texas)
- London Review of Books
- "The Expert"
- Team Andrew Weinberg Walking September 8th for the Jimmy Fund!
- Mrooijer's Numbers R 4Us
- The Keeling Curve: its history History of the Keeling Curve and Charles David Keeling
- Leverhulme Centre for Climate Change Mitigation
- Musings on Quantitative Paleoecology Quantitative methods and palaeoenvironments.
- Subsidies for wind and solar versus subsidies for fossil fuels
- Beautiful Weeds of New York City
- 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.
- 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.
- Fear and Loathing in Data Science Cory Lesmeister’s savage journey to the heart of Big Data
- What If
- Giant vertical monopolies for energy have stopped making sense
- ggplot2 and ggfortify Plotting State Space Time Series with ggplot2 and ggfortify
- WEAPONS OF MATH DESTRUCTION Cathy O’Neil’s WEAPONS OF MATH DESTRUCTION,
- 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/
- SASB Sustainability Accounting Standards Board
- All about models
- OOI Data Nuggets OOI Ocean Data Lab: The Data Nuggets
- 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
- AP Statistics: Sampling, by Michael Porinchak Twin City Schools
- Label Noise

### climate change

- 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.
- weather blocking patterns
- Berkeley Earth Surface Temperature
- ATTP summarizes all that stuff about Committed Warming from AND THEN THERE’S PHYSICS
- HotWhopper: It's excellent. Global warming and climate change. Eavesdropping on the deniosphere, its weird pseudo-science and crazy conspiracy whoppers.
- 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
- "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.
- Bloomberg interactive graph on “What's warming the world''
- SolarLove
- `The unchained goddess' 1958 Bell Telephone Science Hour broadcast regarding, among other things, climate change.
- An open letter to Steve Levitt
- 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.
- The HUMAN-caused greenhouse effect, in under 5 minutes, by Bill Nye
- "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
- MIT's Climate Primer
- World Weather Attribution
- And Then There's Physics
- "A field guide to the climate clowns"
- All Models Are Wrong Dr Tamsin Edwards blog about uncertainty in science, and climate science
- 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
- Dessler's 6 minute Greenhouse Effect video
- Interview with Wally Broecker Interview with Wally Broecker
- History of discovering Global Warming From the American Institute of Physics.
- 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.
- Wally Broecker on climate realism
- 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.
- “Ways to [try to] slow the Solar Century''
- The Scientific Case for Modern Human-caused Global Warming
- Reanalyses.org
- Spectra Energy exposed
- David Appell's early climate science
- Ray Pierrehumbert's site related to "Principles of Planetary Climate" THE book on climate science
- "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.
- Rabett Run Incisive analysis of climate science versus deliberate distraction
- Simple box models and climate forcing IMO one of Tamino’s best posts illustrating climate forcing using simple box models
- 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
- Simple models of climate change
- Andy Zucker's "Climate Change and Psychology"
- The Green Plate Effect Eli Rabett’s “The Green Plate Effect”
- Non-linear feedbacks in climate (discussion of Bloch-Johnson, Pierrehumbert, Abbot paper) Discussion of http://onlinelibrary.wiley.com/wol1/doi/10.1002/2015GL064240/abstract
- Climate Change Denying Organizations
- SOLAR PRODUCTION at Westwood Statistical Studios Generation charts for our home in Westwood, MA
- Anti—Anti-#ClimateEmergency Whether to declare a climate emergency is debatable. But some critics have gone way overboard.
- James Powell on sampling the climate consensus
- Jacobson WWS literature index
- Klaus Lackner (ASU), Silicon Kingdom Holdings (SKH) Capturing CO2 from air at scale
- Mrooijer's Global Temperature Explorer
- On Thomas Edison and Solar Electric Power
- The net average effect of a warming climate is increased aridity (Professor Steven Sherwood)

### 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
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## 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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