Distributed Solar: The Democratizaton of Energy
- Gavin Simpson
- WEAPONS OF MATH DESTRUCTION Cathy O’Neil’s WEAPONS OF MATH DESTRUCTION,
- 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.
- 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.
- Musings on Quantitative Paleoecology Quantitative methods and palaeoenvironments.
- John Cook's reasons to use Bayesian inference
- distributed solar and matching location to need
- 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.
- Carl Safina's blog One of the wisest on Earth
- All about Sankey diagrams
- Earle Wilson
- Ives and Dakos techniques for regime changes in series
- Subsidies for wind and solar versus subsidies for fossil fuels
- "Talking Politics" podcast David Runciman, Helen Thompson
- Nadler Strategy, LLC, on sustainability Thinking about business, efficient and effective management, and business value
- Peter Congdon's Bayesian statistical modeling Peter Congdon’s collection of links pertaining to his several books on Bayesian modeling
- International Society for Bayesian Analysis (ISBA)
- Quotes by Nikola Tesla Quotes by Nikola Tesla, including some of others he greatly liked.
- Dr James Spall's SPSA
- 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.
- "Perpetual Ocean" from NASA GSFC
- Mrooijer's Numbers R 4Us
- Fear and Loathing in Data Science Cory Lesmeister’s savage journey to the heart of Big Data
- Ted Dunning
- Professor David Draper
- Awkward Botany
- Woods Hole Oceanographic Institution (WHOI)
- Brian McGill's Dynamic Ecology blog Quantitative biology with pithy insights regarding applications of statistical methods
- South Shore Recycling Cooperative Materials management, technical assistance and networking, town advocacy, public outreach
- 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/
- 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.
- John Kruschke's "Dong Bayesian data analysis" blog Expanding and enhancing John’s book of same title (now in second edition!)
- Earth Family Beta MIchael Osborne’s blog on Science and the like
- The Keeling Curve: its history History of the Keeling Curve and Charles David Keeling
- OOI Data Nuggets OOI Ocean Data Lab: The Data Nuggets
- Number Cruncher Politics
- Mark Berliner's video lecture "Bayesian mechanistic-statistical modeling with examples in geophysical settings"
- Comprehensive Guide to Bayes Rule
- Gabriel's staircase
- Slice Sampling
- Mertonian norms
- American Statistical Association
- NCAR AtmosNews
- Los Alamos Center for Bayesian Methods
- Beautiful Weeds of New York City
- 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.”
- Earth Family Alpha Michael Osborne’s blog (former Executive at Austin Energy, now Chairman of the Electric Utility Commission for Austin, Texas)
- Thaddeus Stevens quotes As I get older, I admire this guy more and more
- Survey Methodology, Prof Ron Fricker http://faculty.nps.edu/rdfricke/
- AP Statistics: Sampling, by Michael Porinchak Twin City Schools
- Ray Pierrehumbert's site related to "Principles of Planetary Climate" THE book on climate science
- Climate at a glance Current state of the climate, from NOAA
- 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 beach boondoggle Prof Rob Young on how owners of beach property are socializing their risks at costs to all of us, not the least being it seems coastal damage is less than it actually is
- Berkeley Earth Surface Temperature
- Eli on the spectroscopic basis of atmospheric radiation physical chemistry
- Jacobson WWS literature index
- Wind sled Wind sled: A zero carbon way of exploring ice sheets
- The Carbon Cycle The Carbon Cycle, monitored by The Carbon Project
- Rabett Run Incisive analysis of climate science versus deliberate distraction
- 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
- Anti—Anti-#ClimateEmergency Whether to declare a climate emergency is debatable. But some critics have gone way overboard.
- "Getting to the Energy Future We Want," Dr Steven Chu
- Agendaists Eli Rabett’s coining of a phrase
- James Hansen and granddaughter Sophie on moving forward with progress on climate
- Tamino's Open Mind Open Mind: A statistical look at climate, its science, and at science denial
- Sir David King David King’s perspective on climate, and the next thousands of years for humanity
- Non-linear feedbacks in climate (discussion of Bloch-Johnson, Pierrehumbert, Abbot paper) Discussion of http://onlinelibrary.wiley.com/wol1/doi/10.1002/2015GL064240/abstract
- Jacobson WWS literature index
- ATTP summarizes all that stuff about Committed Warming from AND THEN THERE’S PHYSICS
- MIT's Climate Primer
- Solar Gardens Community Power
- Ice and Snow
- 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.
- Interview with Wally Broecker Interview with Wally Broecker
- Bloomberg interactive graph on “What's warming the world''
- Équiterre Equiterre helps build a social movement by encouraging individuals, organizations and governments to make ecological and equitable choices, in a spirit of solidarity.
- 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.
- 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.
- World Weather Attribution
- Andy Zucker's "Climate Change and Psychology"
- The HUMAN-caused greenhouse effect, in under 5 minutes, by Bill Nye
- And Then There's Physics
- 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
- The net average effect of a warming climate is increased aridity (Professor Steven Sherwood)
- Exxon-Mobil statement on UNFCCC COP21
- Spectra Energy exposed
- Social Cost of Carbon
- Klaus Lackner (ASU), Silicon Kingdom Holdings (SKH) Capturing CO2 from air at scale
- Risk and Well-Being
- "Climate science is setttled enough"
- SOLAR PRODUCTION at Westwood Statistical Studios Generation charts for our home in Westwood, MA
- 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
- weather blocking patterns
- `Who to believe on climate change': Simple checks By Bart Verheggen
- "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
- Climate Communication Hassol, Somerville, Melillo, and Hussin site communicating climate to the public
- Climate Change Reports By John and Mel Harte
- Grid parity map for Solar PV in United States
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 Leave a comment
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 1 Comment
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 Leave a comment
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 4 Comments
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 1 Comment
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 Leave a comment
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 Leave a comment
“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 Leave a comment
Bayesian blocks via PELT in R
Notice of Update I have made some changes to the Bayesian Blocks code linked from here, on 24th November 2021. Also I note the coming and going of a “BayesianBlocks” package on CRAN which contained an optinterval function also based upon … 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 3 Comments
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 Leave a comment
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 5 Comments
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 Leave a comment
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 Leave a comment
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 1 Comment