Distributed Solar: The Democratizaton of Energy
Blogroll
- Survey Methodology, Prof Ron Fricker http://faculty.nps.edu/rdfricke/
- American Statistical Association
- Rasmus Bååth's Research Blog Bayesian statistics and data analysis
- 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
- Awkward Botany
- 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
- "Talking Politics" podcast David Runciman, Helen Thompson
- Prediction vs Forecasting: Knaub “Unfortunately, ‘prediction,’ such as used in model-based survey estimation, is a term that is often subsumed under the term ‘forecasting,’ but here we show why it is important not to confuse these two terms.”
- Healthy Home Healthy Planet
- Leverhulme Centre for Climate Change Mitigation
- Los Alamos Center for Bayesian Methods
- OOI Data Nuggets OOI Ocean Data Lab: The Data Nuggets
- Mark Berliner's video lecture "Bayesian mechanistic-statistical modeling with examples in geophysical settings"
- "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.
- 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/
- Beautiful Weeds of New York City
- Charlie Kufs' "Stats With Cats" blog “You took Statistics 101. Now what?”
- 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.
- AP Statistics: Sampling, by Michael Porinchak Twin City Schools
- Peter Congdon's Bayesian statistical modeling Peter Congdon’s collection of links pertaining to his several books on Bayesian modeling
- The Alliance for Securing Democracy dashboard
- Mertonian norms
- Harvard's Project Implicit
- Carl Safina's blog One of the wisest on Earth
- distributed solar and matching location to need
- Bob Altemeyer on authoritarianism (via Dan Satterfield) The science behind the GOP civil war
- All about Sankey diagrams
- WEAPONS OF MATH DESTRUCTION, reviews Reviews of Cathy O’Neil’s new book
- 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/
- Ives and Dakos techniques for regime changes in series
- Thaddeus Stevens quotes As I get older, I admire this guy more and more
- International Society for Bayesian Analysis (ISBA)
- Karl Broman
- "The Expert"
- Quotes by Nikola Tesla Quotes by Nikola Tesla, including some of others he greatly liked.
- The Plastic Pick-Up: Discovering new sources of marine plastic pollution
- 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
- Musings on Quantitative Paleoecology Quantitative methods and palaeoenvironments.
- 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/.
- South Shore Recycling Cooperative Materials management, technical assistance and networking, town advocacy, public outreach
- 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
- Comprehensive Guide to Bayes Rule
- Fear and Loathing in Data Science Cory Lesmeister’s savage journey to the heart of Big Data
- Earle Wilson
- 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”
- Leadership lessons from Lao Tzu
- WEAPONS OF MATH DESTRUCTION Cathy O’Neil’s WEAPONS OF MATH DESTRUCTION,
- 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
- James' Empty Blog
climate change
- Social Cost of Carbon
- Wind sled Wind sled: A zero carbon way of exploring ice sheets
- Exxon-Mobil statement on UNFCCC COP21
- "Betting strategies on fluctuations in the transient response of greenhouse warming" By Risbey, Lewandowsky, Hunter, Monselesan: Betting against climate change on durations of 15+ years is no longer a rational proposition.
- 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.
- James Hansen and granddaughter Sophie on moving forward with progress on climate
- Earth System Models
- 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.
- Ricky Rood's “What would happen to climate if we (suddenly) stopped emitting GHGs today?
- Climate impacts on retail and supply chains
- Energy payback period for solar panels Considering everything, how long do solar panels have to operate to offset the energy used to produce them?
- Mrooijer's Global Temperature Explorer
- 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.
- 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
- 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
- Updating the Climate Science: What path is the real world following? From Professors Makiko Sato & James Hansen of Columbia University
- "Climate science is setttled enough"
- An open letter to Steve Levitt
- `The unchained goddess' 1958 Bell Telephone Science Hour broadcast regarding, among other things, climate change.
- SOLAR PRODUCTION at Westwood Statistical Studios Generation charts for our home in Westwood, MA
- Spectra Energy exposed
- MIT's Climate Primer
- 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
- "A field guide to the climate clowns"
- Climate model projections versus observations
- Ice and Snow
- Simple models of climate change
- David Appell's early climate science
- Rabett Run Incisive analysis of climate science versus deliberate distraction
- Sir David King David King’s perspective on climate, and the next thousands of years for humanity
- "Warming Slowdown?" (part 1 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. In two parts.
- Bloomberg interactive graph on “What's warming the world''
- Documenting the Climate Deniarati at work
- Jacobson WWS literature index
- Warming slowdown discussion
- Grid parity map for Solar PV in United States
- James Powell on sampling the climate consensus
- weather blocking patterns
- RealClimate
- HotWhopper: It's excellent. Global warming and climate change. Eavesdropping on the deniosphere, its weird pseudo-science and crazy conspiracy whoppers.
- `Who to believe on climate change': Simple checks By Bart Verheggen
- Interview with Wally Broecker Interview with Wally Broecker
- The net average effect of a warming climate is increased aridity (Professor Steven Sherwood)
- Équiterre Equiterre helps build a social movement by encouraging individuals, organizations and governments to make ecological and equitable choices, in a spirit of solidarity.
- ATTP summarizes all that stuff about Committed Warming from AND THEN THERE’S PHYSICS
- Agendaists Eli Rabett’s coining of a phrase
- And Then There's Physics
- Wally Broecker on climate realism
Archives
Jan Galkowski
Category Archives: multivariate statistics
“Code for causal inference: Interested in astronomical applications”
via Code for causal inference: Interested in astronomical applications From Professor Ewan Cameron at his Another Astrostatistics Blog.
Posted in American Association for the Advancement of Science, American Statistical Association, astronomy, astrostatistics, causal inference, causation, counterfactuals, epidemiology, experimental design, experimental science, multivariate statistics, prediction, propensity scoring, quantitative biology, quantitative ecology, reproducible research, rhetorical mathematics, rhetorical science, rhetorical statistics, science, statistical ecology, statistical models, statistical regression, statistics
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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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A response to a post on RealClimate
(Updated 2342 EDT, 28 June 2019.) This is a response to a post on RealClimate which primarily concerned economist Ross McKitrick’s op-ed in the Financial Post condemning the geophysical community for disregarding Roger Pielke, Jr’s arguments. Pielke, in that link, … Continue reading
Posted in American Association for the Advancement of Science, American Meteorological Association, American Statistical Association, AMETSOC, Bayesian, climate change, ecology, Ecology Action, environment, evidence, experimental design, Frequentist, global warming, Hyper Anthropocene, machine learning, model comparison, model-free forecasting, multivariate statistics, science, science denier, statistical series, statistics, time series
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Cumulants and the Cornish-Fisher Expansion
“Consider the following.” (Bill Nye the Science Guy) There are random variables drawn from the same kind of probability distribution, but with different parameters for each. In this example, I’ll consider random variables , that is, each drawn from a … Continue reading
Series, symmetrized Normalized Compressed Divergences and their logit transforms
(Major update on 11th January 2019. Minor update on 16th January 2019.) On comparing things The idea of a calculating a distance between series for various purposes has received scholarly attention for quite some time. The most common application is … Continue reading
Posted in Akaike Information Criterion, bridge to somewhere, computation, content-free inference, data science, descriptive statistics, divergence measures, engineering, George Sughihara, information theoretic statistics, likelihood-free, machine learning, mathematics, model comparison, model-free forecasting, multivariate statistics, non-mechanistic modeling, non-parametric statistics, numerical algorithms, statistics, theoretical physics, thermodynamics, time series
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The Johnson-Lindenstrauss Lemma, and the paradoxical power of random linear operators. Part 1.
Updated, 2018-12-04 I’ll be discussing the ramifications of: William B. Johnson and Joram Lindenstrauss, “Extensions of Lipschitz mappings into a Hilbert space, Contemporary Mathematics, 26:189–206, 1984. for several posts here. Some introduction and links to proofs and explications will be … Continue reading
Posted in clustering, data science, dimension reduction, information theoretic statistics, Johnson-Lindenstrauss Lemma, k-NN, Locality Sensitive Hashing, mathematics, maths, multivariate statistics, non-parametric model, numerical algorithms, numerical linear algebra, point pattern analysis, random projections, recommender systems, science, stochastic algorithms, stochastics, subspace projection methods
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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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A quick note on modeling operational risk from count data
The blog statcompute recently featured a proposal encouraging the use of ordinal models for difficult risk regressions involving count data. This is actually a second installment of a two-part post on this problem, the first dealing with flexibility in count … Continue reading
Posted in American Statistical Association, Bayesian, Bayesian computational methods, count data regression, dichotomising continuous variables, dynamic generalized linear models, Frank Harrell, Frequentist, Generalize Additive Models, generalized linear mixed models, generalized linear models, GLMMs, GLMs, John Kruschke, maximum likelihood, model comparison, Monte Carlo Statistical Methods, multivariate statistics, nonlinear, numerical software, numerics, premature categorization, probit regression, statistical regression, statistics
Tagged dichotomising continuous variables, dichotomizing continuous variables, premature categorization, splines
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“Holy crap – an actual book!”
Originally posted on mathbabe:
Yo, everyone! The final version of my book now exists, and I have exactly one copy! Here’s my editor, Amanda Cook, holding it yesterday when we met for beers: Here’s my son holding it: He’s offered…
Posted in American Association for the Advancement of Science, Buckminster Fuller, business, citizen science, citizenship, civilization, complex systems, confirmation bias, data science, data streams, deep recurrent neural networks, denial, economics, education, engineering, ethics, evidence, Internet, investing, life purpose, machine learning, mathematical publishing, mathematics, mathematics education, maths, moral leadership, multivariate statistics, numerical software, numerics, obfuscating data, organizational failures, politics, population biology, prediction, prediction markets, privacy, quantitative biology, quantitative ecology, rationality, reason, reasonableness, rhetoric, risk, Schnabel census, smart data, sociology, statistical dependence, statistics, the right to be and act stupid, the right to know, the value of financial assets, transparency, UU Humanists
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Bayesian blocks via PELT in R
The Bayesian blocks algorithm of Scargle, Jackson, Norris, and Chiang has an enthusiastic user community in astrostatistics, in data mining, and among some in machine learning. It is a dynamic programming algorithm (see VanderPlas referenced below) and, so, exhibits optimality … Continue reading
Posted in American Statistical Association, AMETSOC, anomaly detection, astrophysics, Cauchy distribution, changepoint detection, engineering, geophysics, multivariate statistics, numerical analysis, numerical software, numerics, oceanography, population biology, population dynamics, Python 3, quantitative biology, quantitative ecology, R, Scargle, spatial statistics, square wave approximation, statistics, stepwise approximation, time series, Woods Hole Oceanographic Institution
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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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HadCRUT4 and GISTEMP series filtered and estimated with simple RTS model
Happy Vernal Equinox! This post has been updated today with some of the equations which correspond to the models. An assessment of whether or not there was a meaningful slowdown or “hiatus” in global warming, was recently discussed by Tamino … Continue reading
Posted in AMETSOC, anemic data, Bayesian, boosting, bridge to somewhere, cat1, changepoint detection, climate, climate change, climate data, climate disruption, climate models, complex systems, computation, data science, dynamical systems, geophysics, George Sughihara, global warming, hiatus, information theoretic statistics, machine learning, maths, meteorology, MIchael Mann, multivariate statistics, physics, prediction, Principles of Planetary Climate, rationality, reasonableness, regime shifts, sea level rise, time series
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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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Your future: Antarctica, in detail
Climate and geophysical accuracy demands fine modeling grids, and very large supercomputers. The best and biggest supercomputers have not been available for climate work, until recently. Watch how results differ if fine meshes and big supercomputers are used. Why haven’t … Continue reading
Posted in Antarctica, Anthropocene, bridge to nowhere, climate, climate change, climate disruption, climate zombies, disingenuity, ecology, ensembles, forecasting, geophysics, global warming, Hyper Anthropocene, ignorance, IPCC, Lawrence Berkeley National Laboratory, LBNL, living shorelines, mathematics, mathematics education, maths, mesh models, meteorology, multivariate statistics, numerical software, optimization, physics, rationality, reasonableness, risk, science, science education, sea level rise, spatial statistics, state-space models, statistics, stochastic algorithms, stochastics, supercomputers, temporal myopia, the right to know, thermodynamics, time series, University of California Berkeley, WAIS
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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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ecoquant
