Distributed Solar: The Democratizaton of Energy
Blogroll
- What If
- 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
- Ted Dunning
- Charlie Kufs' "Stats With Cats" blog “You took Statistics 101. Now what?”
- 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/.
- Comprehensive Guide to Bayes Rule
- Peter Congdon's Bayesian statistical modeling Peter Congdon’s collection of links pertaining to his several books on Bayesian modeling
- Mertonian norms
- The Mermaid's Tale A conversation about biological complexity and evolution, and the societal aspects of science
- 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/
- Leverhulme Centre for Climate Change Mitigation
- Earle Wilson
- John Kruschke's "Dong Bayesian data analysis" blog Expanding and enhancing John’s book of same title (now in second edition!)
- Subsidies for wind and solar versus subsidies for fossil fuels
- Gabriel's staircase
- 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
- Los Alamos Center for Bayesian Methods
- London Review of Books
- distributed solar and matching location to need
- 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.
- All about Sankey diagrams
- Brian McGill's Dynamic Ecology blog Quantitative biology with pithy insights regarding applications of statistical methods
- ggplot2 and ggfortify Plotting State Space Time Series with ggplot2 and ggfortify
- AP Statistics: Sampling, by Michael Porinchak Twin City Schools
- 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.
- Survey Methodology, Prof Ron Fricker http://faculty.nps.edu/rdfricke/
- GeoEnergy Math Prof Paul Pukite’s Web site devoted to energy derived from geological and geophysical processes and categorized according to its originating source.
- 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
- "Perpetual Ocean" from NASA GSFC
- Musings on Quantitative Paleoecology Quantitative methods and palaeoenvironments.
- Gavin Simpson
- International Society for Bayesian Analysis (ISBA)
- Carl Safina's blog One of the wisest on Earth
- 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/
- Professor David Draper
- Mrooijer's Numbers R 4Us
- The Plastic Pick-Up: Discovering new sources of marine plastic pollution
- Nadler Strategy, LLC, on sustainability Thinking about business, efficient and effective management, and business value
- 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.
- American Association for the Advancement of Science (AAAS)
- OOI Data Nuggets OOI Ocean Data Lab: The Data Nuggets
- "Consider a Flat Pond" Invited talk introducing systems thinking, by Jan Galkowski, at First Parish in Needham, UU, via Zoom
- Awkward Botany
- American Statistical Association
- All about models
- Rasmus Bååth's Research Blog Bayesian statistics and data analysis
- "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.
- Dominic Cummings blog Chief advisor to the PM, United Kingdom
- Quotes by Nikola Tesla Quotes by Nikola Tesla, including some of others he greatly liked.
- South Shore Recycling Cooperative Materials management, technical assistance and networking, town advocacy, public outreach
climate change
- Social Cost of Carbon
- The HUMAN-caused greenhouse effect, in under 5 minutes, by Bill Nye
- Klaus Lackner (ASU), Silicon Kingdom Holdings (SKH) Capturing CO2 from air at scale
- Équiterre Equiterre helps build a social movement by encouraging individuals, organizations and governments to make ecological and equitable choices, in a spirit of solidarity.
- Ellenbogen: There is no Such Thing as Wind Turbine Syndrome
- MIT's Climate Primer
- "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
- Reanalyses.org
- RealClimate
- Sir David King David King’s perspective on climate, and the next thousands of years for humanity
- Energy payback period for solar panels Considering everything, how long do solar panels have to operate to offset the energy used to produce them?
- On Thomas Edison and Solar Electric Power
- Simple box models and climate forcing IMO one of Tamino’s best posts illustrating climate forcing using simple box models
- Climate impacts on retail and supply chains
- 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 unchained goddess' 1958 Bell Telephone Science Hour broadcast regarding, among other things, climate change.
- Simple models of climate change
- "Lessons of the Little Ice Age" (Farber) From Dan Farber, at LEGAL PLANET
- Ice and Snow
- Skeptical Science
- James Powell on sampling the climate consensus
- Professor Robert Strom's compendium of resources on climate change Truly excellent
- Climate Communication Hassol, Somerville, Melillo, and Hussin site communicating climate to the public
- Bloomberg interactive graph on “What's warming the world''
- Wally Broecker on climate realism
- Climate at a glance Current state of the climate, from NOAA
- Non-linear feedbacks in climate (discussion of Bloch-Johnson, Pierrehumbert, Abbot paper) Discussion of http://onlinelibrary.wiley.com/wol1/doi/10.1002/2015GL064240/abstract
- "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.
- World Weather Attribution
- Jacobson WWS literature index
- Thriving on Low Carbon
- weather blocking patterns
- 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 Carbon Cycle The Carbon Cycle, monitored by The Carbon Project
- Risk and Well-Being
- "Getting to the Energy Future We Want," Dr Steven Chu
- Warming slowdown discussion
- "Climate science is setttled enough"
- Climate Change Reports By John and Mel Harte
- The net average effect of a warming climate is increased aridity (Professor Steven Sherwood)
- The Scientific Case for Modern Human-caused Global Warming
- History of discovering Global Warming From the American Institute of Physics.
- An open letter to Steve Levitt
- 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
- Mrooijer's Global Temperature Explorer
- Dessler's 6 minute Greenhouse Effect video
- Documenting the Climate Deniarati at work
- “Ways to [try to] slow the Solar Century''
- Interview with Wally Broecker Interview with Wally Broecker
- Anti—Anti-#ClimateEmergency Whether to declare a climate emergency is debatable. But some critics have gone way overboard.
Archives
Jan Galkowski
Category Archives: stochastic algorithms
“Unbiased Bayes for Big Data: Path of partial posteriors” (Christian Robert)
Unbiased Bayes for Big Data: Path of partial posteriors.
Dynamic Linear Models package, dlmodeler
I’m checking out the dlmodeler package in R for a work project. It is accompanied by textbooks, G. Petris, S. Petrone, P. Campagnoli, Dynamic Linear Models with R, Springer, 2009 and J. Durbin, S. J. Koopman, Time Series Analysis by … Continue reading
Markov Chain Monte Carlo methods and logistic regression
This post could also be subtitled “Residual deviance isn’t the whole story.” My favorite book on logistic regression is by Dr Joseph Hilbe, Logistic Regression Models, CRC Press, 2009, Chapman & Hill. It is a solidly frequentist text, but its … Continue reading
Posted in Bayes, Bayesian, logistic regression, MCMC, notes, R, statistics, stochastic algorithms, stochastic search
3 Comments
Bayesian change-point analysis for global temperatures, 1850-2010
Professor Peter Congdon reports on two Bayesian models for global temperature shifts in his textbook, Applied Bayesian Modelling, as “Example 6.12: Global temperatures, 1850-2010”, on pages 252-253. A direct link is available online. The first is apparently original with Congdon, … Continue reading
Christian Robert on the amazing Gibbs sampler
Professor Christian Robert remarks on the amazing Gibbs sampler. Implicitly he’s also underscoring the power of properly done Bayesian computational analysis. For here we have a problem with a posterior distribution having two strong modes, so a point estimate, like … Continue reading
Christian Robert on Alan Turing
Alan Turing Institute. See Professor Robert’s earlier post on Turing, too.
Posted in Bayes, Bayesian, citizenship, education, ethics, history, humanism, mathematics, maths, politics, rationality, reasonableness, statistics, stochastic algorithms, stochastic search, the right to know, Wordpress
Tagged Alan Turing
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On nested equivalence classes of climate models, ordered by computational complexity
I’m digging into the internals of ABC, for professional and scientific reasons. I’ve linked a great tutorial elsewhere, and argued that this framework, advanced by Wood, and Wilkinson (Robert), and Wilkinson (Darren), and Hartig and colleagues, and Robert and colleagues, … Continue reading
Posted in approximate Bayesian computation, Bayes, Bayesian, biology, ecology, environment, forecasting, geophysics, IPCC, mathematics, maths, MCMC, meteorology, NCAR, NOAA, oceanography, optimization, population biology, Principles of Planetary Climate, probabilistic programming, R, science, stochastic algorithms, stochastic search
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“[W]e want to model the process as we would simulate it.”
Professor Darren Wilkinson offers a pithy insight on how to go about constructing statistical models, notably hierarchical ones: “… we want to model the process as we would simulate it ….” This appears in his blog post One-way ANOVA with … Continue reading
Posted in approximate Bayesian computation, Bayes, Bayesian, biology, ecology, engineering, forecasting, mathematics, mathematics education, maths, model comparison, optimization, population biology, probabilistic programming, rationality, reasonableness, risk, science, science education, sociology, statistics, stochastic algorithms
Tagged ANOVA
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struggling with problems already partly solved by others
Climate modelers and models see as their frontier the problem of dealing with spontaneous dynamics in systems such as atmosphere or ocean which are not directly forced by boundary conditions such as radiative forcing due to increased greenhouse gas (“GHG”) … Continue reading
Posted in approximate Bayesian computation, Bayes, Bayesian, biology, climate, climate education, differential equations, ecology, engineering, environment, geophysics, IPCC, mathematics, mathematics education, meteorology, model comparison, NCAR, NOAA, oceanography, physics, population biology, probabilistic programming, rationality, reasonableness, risk, science, science education, statistics, stochastic algorithms, stochastic search
1 Comment
illustrating particle filters and Bayesian fusion using successive location estimates on the unit circle
Introduction Modern treatments of Bayesian integration to obtain posterior densities often use some form of Markov Chain Monte Carlo (“MCMC”), typically Gibbs sampling. Gibbs works well with many Bayesian hierarchical models. The standard problem-solving situation with these is that a … Continue reading
Bayesian inference works even in a chaotic or deterministic world
Professor John Geweke, in a Comment on an article by Professor Mark Berliner a bit back (1992), shows how Bayesian inference continues to be a means for expressing subjective uncertainty even in a scheme where there are no stochastics but … Continue reading
Understanding mechanisms in climate over short periods and in local regions
This is interesting, because it shows how any particular observational history of Earth is one election of a large number of possible futures. This is exactly the same point made by Slava Kharin in his 2008 tutorial lecture “Statistical concepts … Continue reading
Posted in carbon dioxide, climate, climate education, differential equations, ecology, energy, environment, forecasting, geophysics, IPCC, mathematics, mathematics education, maths, meteorology, NCAR, NOAA, oceanography, physics, rationality, reasonableness, science, statistics, stochastic algorithms
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“Can we trust climate models?”
J. C. Hargreaves, J. D. Annan, “Can we trust climate models?”, WIREs Climate Change 2014, 5:435–440. doi: 10.1002/wcc.288. See also D. A. Stainforth, T. Aina, C. Christensen, M. Collins, N. Faull, D. J. Frame, J. A. Kettleborough, S. Knight, A. … Continue reading
Bayesian deconvolution of stick lengths
Consider trying to determine the length of a straight stick. Instead of the measurement errors being clustered about zero, suppose the errors are known to be always positive, that is, no measurement ever underestimates the length of the stick. Such … Continue reading
Brendon Brewer on “Hard Integrals”
Hard Integrals.
Posted in Bayesian, mathematics, maths, statistics, stochastic algorithms
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The dp-means algorithm of Kulis and Jordan in R and Python
dp-means algorithm. Think k-means but with the number of clusters calculated. By John Myles White, in R. (Github link off that page.) By Scott Hendrickson, in Python. (Github link off that page.)
Posted in Bayesian, Gibbs Sampling, JAGS, mathematics, maths, R, statistics, stochastic algorithms, stochastic search
Tagged dp-means
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Blind Bayesian recovery of components of residential solid waste tonnage from totals data
This is a sketch of how maths and statistics can do something called blind source separation, meaning to estimate the components of data given only their totals. Here, I use Bayesian techniques for the purpose, sometimes called Bayesian inversion, using … Continue reading
singingbanana does “The Lorenz Machine”
On the power of mathematics, and why 55:45 versus 50:50 matters.
Posted in Bayesian, engineering, mathematics, maths, rationality, reasonableness, risk, stochastic algorithms, stochastic search
Tagged code breaking
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“The joy and martyrdom of trying to be a Bayesian”
Bayesians have all been there. Some of us don’t depend upon producing publications to assure our pay, so we less have the pressure of pleasing peer reviewers. Nonetheless, it’s all reacting to “What the hell are you doing? I don’t … Continue reading
How fast is JAGS?
How fast is JAGS?.
Comment on “Timescales for detecting a significant acceleration in sea level rise” by Haigh, et al
Amended, 1st May 2014. The lead author, Dr Ivan Haigh, and I have had a very friendly discussion this paper and its context in detail. Now that I understand the context, and especially the atrocious maths of the Houston, Dean, … Continue reading
Posted in Bayesian, climate, forecasting, geophysics, mathematics, maths, meteorology, physics, rationality, science, statistics, stochastic algorithms
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Comment on “How urban anonymity disappears when all data is tracked”, an article in the NY Times
The New York Times has an article titled “How urban anonymity disappears when all data is tracked” by Quentin Hardy which appears in its “Bits” section. I just posted a comment on that article, which is reproduced below: I hope … Continue reading
JAGS for finding Highs and Lows in a week of Wikipedia accesses
I’ve been learning how to use JAGS for Bayesian hierarchical modeling, moved by the great teaching of John Kruschke, Peter Congdon, Andrew Gelman, and many others. So, I went on to solve a problem with JAGS (“Just Another Gibbs Sampler”). … Continue reading
Posted in Bayesian, Internet, statistics, stochastic algorithms
Tagged stats.grok.se, Wikipedia
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postdoc position in Bayesian Climate Uncertainty Modeling
Climate Uncertainty Quantification Postdoc Where You Will Work Located in northern New Mexico, Los Alamos National Laboratory (LANL) is a multidisciplinary research institution engaged in strategic science on behalf of national security. LANL enhances national security by ensuring the safety … Continue reading
Posted in Bayesian, climate, environment, geophysics, mathematics, maths, meteorology, physics, statistics, stochastic algorithms
Tagged climate uncertainty, postdoc, statistics
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Correlation, causation, and coupled pairs of differential equations
An aspect of paleoclimate evidence to which Professor Jennifer Francis alludes in her recent report on Arctic amplification is the close mutual modeling which Earth surface temperature and carbon dioxide concentration exhibit during the recent geologic past. Since relative timings … Continue reading
Bayesian Bootstrap
I’m studying the Bayesian bootstrap in the context of finite population sampling for an application where I need to estimate multinomial proportions. While I have used the frequentist bootstrap a lot, it has bothered me that it can never, of … Continue reading
Posted in Bayesian, mathematics, maths, statistics, stochastic algorithms
3 Comments
“Double Plus Big Data”
Big Data. All the rage. Why? Apart from distributed software folks strutting their stuff, something which is likely to be fleeting, especially when quantum computing comes around, what does it buy anyone? I can see four possibilities, which I consider … Continue reading
“Bayes’ theorem in the 21st century”
Professor Bradley Efron wrote a piece on “Bayes’ theorem in the 21st century” in Science for 7th June 2013 which, as always, offers his measured approach to the frequentist-Bayesian controversy (see B. Efron, “A 250 year argument: Belief, behavior, and the … Continue reading
ecoquant
