Distributed Solar: The Democratizaton of Energy
Blogroll
- 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.
- Dollars per BBL: Energy in Transition
- Leadership lessons from Lao Tzu
- Earth Family Beta MIchael Osborne’s blog on Science and the like
- Dominic Cummings blog Chief advisor to the PM, United Kingdom
- Nadler Strategy, LLC, on sustainability Thinking about business, efficient and effective management, and business value
- Awkward Botany
- Slice Sampling
- All about models
- American Association for the Advancement of Science (AAAS)
- NCAR AtmosNews
- BioPython A collection of Python tools for quantitative Biology
- Woods Hole Oceanographic Institution (WHOI)
- John Cook's reasons to use Bayesian inference
- 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.
- Label Noise
- The Mermaid's Tale A conversation about biological complexity and evolution, and the societal aspects of science
- AP Statistics: Sampling, by Michael Porinchak Twin City Schools
- Survey Methodology, Prof Ron Fricker http://faculty.nps.edu/rdfricke/
- "The Expert"
- Brian McGill's Dynamic Ecology blog Quantitative biology with pithy insights regarding applications of statistical methods
- 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.
- American Statistical Association
- John Kruschke's "Dong Bayesian data analysis" blog Expanding and enhancing John’s book of same title (now in second edition!)
- Gabriel's staircase
- Charlie Kufs' "Stats With Cats" blog “You took Statistics 101. Now what?”
- Giant vertical monopolies for energy have stopped making sense
- All about Sankey diagrams
- Rasmus Bååth's Research Blog Bayesian statistics and data analysis
- Earth Family Alpha Michael Osborne’s blog (former Executive at Austin Energy, now Chairman of the Electric Utility Commission for Austin, Texas)
- What If
- "Talking Politics" podcast David Runciman, Helen Thompson
- James' Empty Blog
- 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
- Quotes by Nikola Tesla Quotes by Nikola Tesla, including some of others he greatly liked.
- 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 Keeling Curve: its history History of the Keeling Curve and Charles David Keeling
- 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/
- South Shore Recycling Cooperative Materials management, technical assistance and networking, town advocacy, public outreach
- Brendon Brewer on Overfitting Important and insightful presentation by Brendon Brewer on overfitting
- OOI Data Nuggets OOI Ocean Data Lab: The Data Nuggets
- Healthy Home Healthy Planet
- 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
- Harvard's Project Implicit
- Team Andrew Weinberg Walking September 8th for the Jimmy Fund!
- 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
- Gavin Simpson
- WEAPONS OF MATH DESTRUCTION Cathy O’Neil’s WEAPONS OF MATH DESTRUCTION,
- Professor David Draper
- 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.
climate change
- Social Cost of Carbon
- Tuft's Professor Kenneth Lang on the physical chemistry of the Greenhouse Effect
- The HUMAN-caused greenhouse effect, in under 5 minutes, by Bill Nye
- Documenting the Climate Deniarati at work
- "Climate science is setttled enough"
- 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.
- Non-linear feedbacks in climate (discussion of Bloch-Johnson, Pierrehumbert, Abbot paper) Discussion of http://onlinelibrary.wiley.com/wol1/doi/10.1002/2015GL064240/abstract
- "Getting to the Energy Future We Want," Dr Steven Chu
- Sir David King David King’s perspective on climate, and the next thousands of years for humanity
- 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.
- `The unchained goddess' 1958 Bell Telephone Science Hour broadcast regarding, among other things, climate change.
- The Green Plate Effect Eli Rabett’s “The Green Plate Effect”
- Skeptical Science
- Bloomberg interactive graph on “What's warming the world''
- SOLAR PRODUCTION at Westwood Statistical Studios Generation charts for our home in Westwood, MA
- "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.
- RealClimate
- ATTP summarizes all that stuff about Committed Warming from AND THEN THERE’S PHYSICS
- Eli on the spectroscopic basis of atmospheric radiation physical chemistry
- Nick Bower's "Scared Scientists"
- Climate at a glance Current state of the climate, from NOAA
- "A field guide to the climate clowns"
- Ray Pierrehumbert's site related to "Principles of Planetary Climate" THE book on climate science
- Climate Change Denying Organizations
- Tamino's Open Mind Open Mind: A statistical look at climate, its science, and at science denial
- 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.
- 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
- Solar Gardens Community Power
- "Lessons of the Little Ice Age" (Farber) From Dan Farber, at LEGAL PLANET
- 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.
- Agendaists Eli Rabett’s coining of a phrase
- Simple models of climate change
- On Thomas Edison and Solar Electric Power
- Ricky Rood's “What would happen to climate if we (suddenly) stopped emitting GHGs today?
- Interview with Wally Broecker Interview with Wally Broecker
- Jacobson WWS literature index
- 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
- 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
- All Models Are Wrong Dr Tamsin Edwards blog about uncertainty in science, and climate science
- Climate model projections versus observations
- 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 Scientific Case for Modern Human-caused Global Warming
- "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
- And Then There's Physics
- Climate Communication Hassol, Somerville, Melillo, and Hussin site communicating climate to the public
- Exxon-Mobil statement on UNFCCC COP21
- James Powell on sampling the climate consensus
- 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%.
- 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.
Archives
Jan Galkowski
Category Archives: Bayes
Oldie and Goodie: `Testing a point Null Hypothesis: The irreconcilability of p-values and evidence’
A blog post by Professor Christian Robert mentioned a paper by Professors James Berger and Tom Sellke, which I downloaded several years back but never got around to reading. J. O. Berger, T. M. Sellke, “Testing a point Null Hypothesis: … Continue reading
Posted in American Statistical Association, Bayes, Bayesian, p-value
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cdetools package for R: Dalmasso, et al [updated]
Just hit the “arXiv streets”: N. Dalmasso, T. Pospisil, A. B. Lee, R. Izbicki, P. E. Freeman, A. I. Malz, “Conditional Density Estimation Tools in Python and R with applications to photometric redshifts and likelihood-free cosmological inference”, arXiv.org > astro-ph … Continue reading
perceptions of likelihood
That’s from this Github repository, maintained by Zoni Nation, having this description. The original data are from a study by Sherman Kent at the U.S. CIA, and is quoted in at least once outside source discussing the problem. In addition … Continue reading
Merry Newtonmas tomorrow! On finding the area of the Batman Shape using Monte Carlo integration
It’s Newtonmas 2017 tomorrow! What better way to celebrate than talk about integration! The Batman Shape (sometimes called the Batman Curve, somewhat erroneously, I think) looks like this: You can find details about it at Wolfram MathWorld, including its area … Continue reading
Posted in Bayes, Calculus, Markov Chain Monte Carlo
Tagged Batman Curve, Batman Shape, James Schloss, Monte Carlo integration, slice sampling
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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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Newt Gingrich and Van Jones. Right on.
It’s the thing. And it addresses how media and people forget about the actual statistics, and focus on the White Hot Bright Light. A study by Gelman, Fagan, and Kiss A study by Freyer A counterpoint to the Freyer study … Continue reading
Posted in American Statistical Association, Bayes, Bayesian, citizen science, criminal justice, Daniel Kahneman, ethics, evidence, fear uncertainty and doubt, humanism, Lives Matter, logistic regression, Markov Chain Monte Carlo, MCMC, organizational failures, population biology, rationality, reasonableness, risk, statistics, Susan Jacoby, 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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Cory Lesmeister’s treatment of Simson’s Paradox (at “Fear and Loathing in Data Science”)
(Updated 2016-05-08, to provide reference for plateaus of ML functions in vicinity of MLE.) Simpson’s Paradox is one of those phenomena of data which really give Statistics a substance and a role, beyond the roles it inherits from, say, theoretical … Continue reading
Posted in Akaike Information Criterion, approximate Bayesian computation, Bayes, Bayesian, evidence, Frequentist, games of chance, information theoretic statistics, Kalman filter, likelihood-free, mathematics, maths, maximum likelihood, Monte Carlo Statistical Methods, probabilistic programming, rationality, Rauch-Tung-Striebel, Simpson's Paradox, state-space models, statistical dependence, statistics, stochastics
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“Lucky d20” (by Tamino, with my reblogging comments)
Originally posted on Open Mind:
What with talk of killer heat waves, droughts, floods, etc. etc., this blog tends to get pretty serious. When it does, we don’t deal with happy prospects, but with the danger of worldwide catastrophe. But…
p-values and hypothesis tests: the Bayesian(s) rule
The American Statistical Association of which I am a longtime member issued an important statement today which will hopefully move statistical practice in engineering and especially in the sciences away from the misleading practice of using p-values and hypothesis tests. … Continue reading
Posted in approximate Bayesian computation, arXiv, Bayes, Bayesian, Bayesian inversion, bollocks, Christian Robert, climate, complex systems, data science, Frequentist, information theoretic statistics, likelihood-free, Markov Chain Monte Carlo, MCMC, Monte Carlo Statistical Methods, population biology, rationality, reasonableness, science, scientific publishing, statistical dependence, statistics, stochastics, Student t distribution
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high dimension Metropolis-Hastings algorithms
If attempting to simulate from a multivariate standard normal distribution in a large dimension, when starting from the mode of the target, i.e., its mean γ, leaving the mode γis extremely unlikely, given the huge drop between the value of the density at the mode γ and at likely realisations Continue reading
Posted in Bayes, Bayesian, Bayesian inversion, boosting, chance, Christian Robert, computation, ensembles, Gibbs Sampling, James Spall, Jerome Friedman, Markov Chain Monte Carlo, mathematics, maths, MCMC, Monte Carlo Statistical Methods, multivariate statistics, numerical software, numerics, optimization, reasonableness, Robert Schapire, SPSA, state-space models, statistics, stochastic algorithms, stochastic search, stochastics, Yoav Freund
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Generating supports for classification rules in black box regression models
Inspired by the extensive and excellent work in approximate Bayesian computation (see also), especially that done by Professors Christian Robert and colleagues (see also), and Professor Simon Wood (see also), it occurred to me that the complaints regarding lack of … Continue reading
Posted in approximate Bayesian computation, Bayes, Bayesian, Bayesian inversion, generalized linear models, machine learning, numerical analysis, numerical software, probabilistic programming, rationality, reasonableness, state-space models, statistics, stochastic algorithms, stochastic search, stochastics, support of black boxes
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R and “big data”
On 2nd November 2015, Wes McKinney, the developer of the highly useful Python pandas module (and other things, including books), wrote an amusing blog post, “The problem with the data science language wars“. I by no means disagree with him. … Continue reading
On differential localization of tumors using relative concentrations of ctDNA. Part 2.
Part 1 of this series introduced the idea of ctDNA and its use for detecting cancers or their resurgence, and proposed a scheme whereby relative concentrations of ctDNA at two or more sites after controlled disturbance might be used to … Continue reading
Deep Recurrent Learning Networks
(Also known to statisticians as deep exponential families.) Large scale deep learning Four easy lessons on Deep Learning from Google
Posted in Bayes, Bayesian, neural networks, optimization
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Comprehensive and compact tutorial on Petris’ DLM package in R; with an update about Helske’s KFAS
A blogger named Lalas produced on Quantitative Thoughts a very comprehensive and compact tutorial on the R package dlm by Petris. I use dlm a lot. Unfortunately, Lalas does not give details on how the SVD is used. They do … Continue reading
Posted in Bayes, Bayesian, dynamic linear models, dynamical systems, forecasting, Kalman filter, mathematics, maths, multivariate statistics, numerical software, open source scientific software, prediction, R, Rauch-Tung-Striebel, state-space models, statistics, stochastic algorithms, SVD, time series
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“Cauchy Distribution: Evil or Angel?” (from Xian)
Cauchy Distribution: Evil or Angel?. From Professor Christian Robert.
“… the most patronizing start to an answer I have ever received …”
Professor Christian Robert tries to help out a student of MCMC on Cross Validated and earns the comment that his help had “the most patronizing start to an answer I have ever received“. I learned a new term: primitivus petitor.
“A vignette on Metropolis” (Christian Robert)
Originally posted on Xi'an's Og:
Over the past week, I wrote a short introduction to the Metropolis-Hastings algorithm, mostly in the style of our Introduction to Monte Carlo with R book, that is, with very little theory and…
“Unbiased Bayes for Big Data: Path of partial posteriors” (Christian Robert)
Unbiased Bayes for Big Data: Path of partial posteriors.
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
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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
“Big Data is the new Phrenology”
From mathbabe: Big Data is the new phrenology. Excerpt: Here’s the thing. What we’ve got is a new kind of awful pseudo-science, which replaces measurements of skulls with big data. There’s no reason to think this stuff is any less … Continue reading
Posted in anemic data, Bayes, Bayesian, bridge to nowhere, mathematics, maths, rationality, reasonableness, statistics
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R vs Python: Practical Data Analysis
R vs Python: Practical Data Analysis (Nonlinear Regression).
Posted in Bayes, Bayesian, biology, climate change, ecology, environment, Python 3, R, statistics, Wordpress
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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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Richard Muller: “I Was Wrong On Global Warming, But It Didn’t Convince The ‘Sceptics'”
Update. 26th February 2015 This is not directly related to the BEST project described in the YouTube video above, but the Berkeley National Laboratory has experimentally linked increases in radiative forcing with increases in atmospheric concentrations of CO2 due to … Continue reading
Posted in astrophysics, Bayes, carbon dioxide, citizenship, civilization, climate, climate change, climate education, differential equations, ecology, environment, geoengineering, geophysics, IPCC, mathematics, maths, meteorology, model comparison, NASA, NCAR, NOAA, oceanography, physics, population biology, rationality, Ray Pierrehumbert, reasonableness, reproducible research, risk, science, science education, sea level rise, the right to know
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ecoquant
667 per centimeter : climate science, quantitative biology, statistics, and energy policy 