Distributed Solar: The Democratizaton of Energy
Blogroll
- Slice Sampling
- Quotes by Nikola Tesla Quotes by Nikola Tesla, including some of others he greatly liked.
- Harvard's Project Implicit
- 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.
- The Alliance for Securing Democracy dashboard
- 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.
- Number Cruncher Politics
- Brendon Brewer on Overfitting Important and insightful presentation by Brendon Brewer on overfitting
- Healthy Home Healthy Planet
- International Society for Bayesian Analysis (ISBA)
- 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.
- London Review of Books
- 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.
- Charlie Kufs' "Stats With Cats" blog “You took Statistics 101. Now what?”
- American Statistical Association
- The Plastic Pick-Up: Discovering new sources of marine plastic pollution
- distributed solar and matching location to need
- "Perpetual Ocean" from NASA GSFC
- 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
- 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
- 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
- Bob Altemeyer on authoritarianism (via Dan Satterfield) The science behind the GOP civil war
- Higgs from AIR describing NAO and EA Stephanie Higgs from AIR Worldwide gives a nice description of NAO and EA in the context of discussing “The Geographic Impact of Climate Signals on European Winter Storms”
- 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/.
- 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
- WEAPONS OF MATH DESTRUCTION Cathy O’Neil’s WEAPONS OF MATH DESTRUCTION,
- "Consider a Flat Pond" Invited talk introducing systems thinking, by Jan Galkowski, at First Parish in Needham, UU, via Zoom
- "Talking Politics" podcast David Runciman, Helen Thompson
- The Mermaid's Tale A conversation about biological complexity and evolution, and the societal aspects of science
- John Cook's reasons to use Bayesian inference
- AP Statistics: Sampling, by Michael Porinchak Twin City Schools
- Flettner Rotor Bruce Yeany introduces the Flettner Rotor and related science
- Musings on Quantitative Paleoecology Quantitative methods and palaeoenvironments.
- Ted Dunning
- Rasmus Bååth's Research Blog Bayesian statistics and data analysis
- Carl Safina's blog One of the wisest on Earth
- Dr James Spall's SPSA
- Los Alamos Center for Bayesian Methods
- All about models
- GeoEnergy Math Prof Paul Pukite’s Web site devoted to energy derived from geological and geophysical processes and categorized according to its originating source.
- Mertonian norms
- South Shore Recycling Cooperative Materials management, technical assistance and networking, town advocacy, public outreach
- Peter Congdon's Bayesian statistical modeling Peter Congdon’s collection of links pertaining to his several books on Bayesian modeling
- Awkward Botany
- Earle Wilson
- What If
- Risk and Well-Being
- OOI Data Nuggets OOI Ocean Data Lab: The Data Nuggets
- Subsidies for wind and solar versus subsidies for fossil fuels
- Mrooijer's Numbers R 4Us
climate change
- Ellenbogen: There is no Such Thing as Wind Turbine Syndrome
- Tuft's Professor Kenneth Lang on the physical chemistry of the Greenhouse Effect
- “The Irrelevance of Saturation: Why Carbon Dioxide Matters'' (Bart Levenson)
- MIT's Climate Primer
- History of discovering Global Warming From the American Institute of Physics.
- Grid parity map for Solar PV in United States
- Reanalyses.org
- Climate Change Denying Organizations
- 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.
- SOLAR PRODUCTION at Westwood Statistical Studios Generation charts for our home in Westwood, MA
- "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
- An open letter to Steve Levitt
- Mrooijer's Global Temperature Explorer
- Exxon-Mobil statement on UNFCCC COP21
- HotWhopper: It's excellent. Global warming and climate change. Eavesdropping on the deniosphere, its weird pseudo-science and crazy conspiracy whoppers.
- Tell Utilities Solar Won't Be Killed Barry Goldwater, Jr’s campaign to push for solar expansion against monopolistic utilities, as a Republican
- The Scientific Case for Modern Human-caused Global Warming
- Professor Robert Strom's compendium of resources on climate change Truly excellent
- Berkeley Earth Surface Temperature
- ATTP summarizes all that stuff about Committed Warming from AND THEN THERE’S PHYSICS
- Tamino's Open Mind Open Mind: A statistical look at climate, its science, and at science denial
- Climate at a glance Current state of the climate, from NOAA
- Warming slowdown discussion
- 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.
- Anti—Anti-#ClimateEmergency Whether to declare a climate emergency is debatable. But some critics have gone way overboard.
- Climate Communication Hassol, Somerville, Melillo, and Hussin site communicating climate to the public
- Nick Bower's "Scared Scientists"
- World Weather Attribution
- 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%.
- "Getting to the Energy Future We Want," Dr Steven Chu
- Spectra Energy exposed
- Earth System Models
- Bloomberg interactive graph on “What's warming the world''
- 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 discovery of global warming'' (American Institute of Physics)
- Jacobson WWS literature index
- The Green Plate Effect Eli Rabett’s “The Green Plate Effect”
- James Powell on sampling the climate consensus
- Social Cost of Carbon
- Climate impacts on retail and supply chains
- SolarLove
- Climate model projections versus observations
- The Carbon Cycle The Carbon Cycle, monitored by The Carbon Project
- Skeptical Science
- Solar Gardens Community Power
- Wind sled Wind sled: A zero carbon way of exploring ice sheets
- Wally Broecker on climate realism
- David Appell's early climate science
- 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.
- The HUMAN-caused greenhouse effect, in under 5 minutes, by Bill Nye
Archives
Jan Galkowski
Category Archives: sampling
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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COVID-19 statistics, a caveat : Sources of data matter
There are a number of sources of COVID-19-related demographics, cases, deaths, numbers testing positive, numbers recovered, and numbers testing negative available. Many of these are not consistent with one another. One could hope at least rates would be consistent, but … Continue reading
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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“Ten Fatal Flaws in Data Analysis” (Charles Kufs)
Professor Kufs has a fun book, Stats with Cats, and a blog. He also has a blog post tiled “Ten Fatal Flaws in Data Analysis” which, in general, I like. But the presentation has some shortcomings, too, which I note … Continue reading
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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Senn’s `… never having to say you are certain’ guest post from Mayo’s blog
via S. Senn: Being a statistician means never having to say you are certain (Guest Post) See also: E. Cai’s blog post “Applied Statistics Lesson of the Day – The Matched Pairs Experimental Design”, from February 2014 A. Deaton, N. … Continue reading
Posted in abstraction, American Association for the Advancement of Science, American Statistical Association, cancer research, data science, ecology, experimental design, generalized linear mixed models, generalized linear models, Mathematics and Climate Research Network, medicine, sampling, statistics, the right to know
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Eli on “Tom [Karl]’s trick and experimental design“
A very fine post at Eli’s blog for students of statistics, meteorology, and climate (like myself) titled: Tom’s trick and experimental design Excerpt: This and the graph from Menne at the top shows that Karl’s trick is working. Although we … Continue reading
Posted in American Meteorological Association, American Statistical Association, AMETSOC, anomaly detection, climate, climate change, climate data, data science, evidence, experimental design, generalized linear mixed models, GISTEMP, GLMMs, global warming, model comparison, model-free forecasting, reblog, sampling, sampling networks
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“Bigger Isn’t Always Better When It Comes to Data”: Barry Nussbaum
The President’s Corner in the May 2017 issue of Amstat News, the monthly newsletter of the American Statistical Association (“ASA”), features the interesting exposition by environmental statistician and President of the ASA, Barry Nussbaum, called “Bigger isn’t always better when … Continue reading
David Spiegelhalter on `how to spot a dodgy statistic’
In this political season, it’s useful to brush up on rhetorical skills, particularly ones involving numbers and statistics, or what John Allen Paulos called numeracy. Professor David Spiegelhalter has written a guide to some of these tricks. Read the whole … Continue reading
Posted in abstraction, anemic data, Bayes, Bayesian, chance, citizenship, civilization, corruption, Daniel Kahneman, disingenuity, Donald Trump, education, games of chance, ignorance, maths, moral leadership, obfuscating data, open data, perceptions, politics, rationality, reason, reasonableness, rhetoric, risk, sampling, science, sociology, statistics, the right to know
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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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“Catching long tail distribution” (Ted Dunning)
One of the best presentations on what can happen if someone takes a naive approach to network data. It also highlights what is, to my mind, the greatly underappreciated t-distribution, which is typically only used in connection with frequentist Student … Continue reading
Going down to the Southern Ocean, by Earle Wilson (on the Scripps R/V Roger Revelle)
(Click on picture to see a larger image, and use your browser Back button to return to reading.) Getting steady data from the Earth’s oceans demands commitment and not a little courage. I could never do what these oceanographers do, … Continue reading
Posted in Alison M Macdonald, anemic data, Antarctica, climate data, complex systems, Earle Wilson, Emily Shuckburgh, engineering, environment, fluid dynamics, geophysics, marine biology, NOAA, oceanic eddies, oceanography, open data, Principles of Planetary Climate, sampling, science, Scripps Institution of Oceanography, thermohaline circulation, waves, WHOI, Woods Hole Oceanographic Institution
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Ah, Hypergeometric!
(“Ah, Hypergeometric!” To be said with the same resignation and acceptance as in “I’ll burn my books–Ah, Mephistopheles!” from Faust.)😉 Dr John Cook, eminent all ’round statistician (with a specialty in biostatistics) and statistical consultant, took up a comment I … Continue reading
ecoquant
