Distributed Solar: The Democratizaton of Energy
Blogroll
- John Cook's reasons to use Bayesian inference
- The Mermaid's Tale A conversation about biological complexity and evolution, and the societal aspects of science
- Healthy Home Healthy Planet
- South Shore Recycling Cooperative Materials management, technical assistance and networking, town advocacy, public outreach
- Quotes by Nikola Tesla Quotes by Nikola Tesla, including some of others he greatly liked.
- Musings on Quantitative Paleoecology Quantitative methods and palaeoenvironments.
- Earle Wilson
- 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/
- Carl Safina's blog One of the wisest on Earth
- Nadler Strategy, LLC, on sustainability Thinking about business, efficient and effective management, and business value
- Dollars per BBL: Energy in Transition
- Beautiful Weeds of New York City
- Earth Family Alpha Michael Osborne’s blog (former Executive at Austin Energy, now Chairman of the Electric Utility Commission for Austin, Texas)
- Comprehensive Guide to Bayes Rule
- Bob Altemeyer on authoritarianism (via Dan Satterfield) The science behind the GOP civil war
- International Society for Bayesian Analysis (ISBA)
- All about models
- distributed solar and matching location to need
- 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.
- Ives and Dakos techniques for regime changes in series
- Fear and Loathing in Data Science Cory Lesmeister’s savage journey to the heart of Big Data
- AP Statistics: Sampling, by Michael Porinchak Twin City Schools
- 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
- BioPython A collection of Python tools for quantitative Biology
- Earth Family Beta MIchael Osborne’s blog on Science and the like
- Leadership lessons from Lao Tzu
- Giant vertical monopolies for energy have stopped making sense
- Peter Congdon's Bayesian statistical modeling Peter Congdon’s collection of links pertaining to his several books on Bayesian modeling
- The Plastic Pick-Up: Discovering new sources of marine plastic pollution
- "Consider a Flat Pond" Invited talk introducing systems thinking, by Jan Galkowski, at First Parish in Needham, UU, via Zoom
- Charlie Kufs' "Stats With Cats" blog “You took Statistics 101. Now what?”
- Ted Dunning
- Rasmus Bååth's Research Blog Bayesian statistics and data analysis
- Dominic Cummings blog Chief advisor to the PM, United Kingdom
- SASB Sustainability Accounting Standards Board
- Professor David Draper
- Mertonian norms
- Slice Sampling
- Subsidies for wind and solar versus subsidies for fossil fuels
- Dr James Spall's SPSA
- Thaddeus Stevens quotes As I get older, I admire this guy more and more
- 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.”
- WEAPONS OF MATH DESTRUCTION Cathy O’Neil’s WEAPONS OF MATH DESTRUCTION,
- American Association for the Advancement of Science (AAAS)
- 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
- WEAPONS OF MATH DESTRUCTION, reviews Reviews of Cathy O’Neil’s new book
- Mrooijer's Numbers R 4Us
- London Review of Books
- Flettner Rotor Bruce Yeany introduces the Flettner Rotor and related science
- James' Empty Blog
climate change
- 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
- Climate Change Denying Organizations
- Skeptical Science
- Updating the Climate Science: What path is the real world following? From Professors Makiko Sato & James Hansen of Columbia University
- “Ways to [try to] slow the Solar Century''
- Tuft's Professor Kenneth Lang on the physical chemistry of the Greenhouse Effect
- "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.
- 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
- World Weather Attribution
- The net average effect of a warming climate is increased aridity (Professor Steven Sherwood)
- Solar Gardens Community Power
- Climate Change Reports By John and Mel Harte
- Tell Utilities Solar Won't Be Killed Barry Goldwater, Jr’s campaign to push for solar expansion against monopolistic utilities, as a Republican
- "A field guide to the climate clowns"
- Simple models of climate change
- "Getting to the Energy Future We Want," Dr Steven Chu
- An open letter to Steve Levitt
- 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.
- Wind sled Wind sled: A zero carbon way of exploring ice sheets
- Wally Broecker on climate realism
- Social Cost of Carbon
- “The discovery of global warming'' (American Institute of Physics)
- Anti—Anti-#ClimateEmergency Whether to declare a climate emergency is debatable. But some critics have gone way overboard.
- Exxon-Mobil statement on UNFCCC COP21
- weather blocking patterns
- `Who to believe on climate change': Simple checks By Bart Verheggen
- Agendaists Eli Rabett’s coining of a phrase
- Reanalyses.org
- Simple box models and climate forcing IMO one of Tamino’s best posts illustrating climate forcing using simple box models
- ATTP summarizes all that stuff about Committed Warming from AND THEN THERE’S PHYSICS
- James Hansen and granddaughter Sophie on moving forward with progress on climate
- On Thomas Edison and Solar Electric Power
- 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.
- Transitioning to fully renewable energy Professor Saul Griffiths talks to transitioning the customer journey, from a dependency upon fossil fuels to an electrified future
- 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.
- Climate at a glance Current state of the climate, from NOAA
- Professor Robert Strom's compendium of resources on climate change Truly excellent
- Climate impacts on retail and supply chains
- 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.
- 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.
- Mrooijer's Global Temperature Explorer
- 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
- Eli on the spectroscopic basis of atmospheric radiation physical chemistry
- “The Irrelevance of Saturation: Why Carbon Dioxide Matters'' (Bart Levenson)
- And Then There's Physics
- Climate model projections versus observations
- All Models Are Wrong Dr Tamsin Edwards blog about uncertainty in science, and climate science
- Équiterre Equiterre helps build a social movement by encouraging individuals, organizations and governments to make ecological and equitable choices, in a spirit of solidarity.
- Energy payback period for solar panels Considering everything, how long do solar panels have to operate to offset the energy used to produce them?
- David Appell's early climate science
Archives
Jan Galkowski
Category Archives: stochastic algorithms
Baseload is an intellectual crutch for engineers and utility managers who cannot think dynamically
This is an awesome presentation by Professor Joshua Pearce of Michigan Technological University. (h/t Peter Sinclair’s Climate Denial Crock of the Week) The same idea, that “baseload is a shortcut for engineers who can’t think dynamically”, was similar in the … Continue reading
Posted in American Solar Energy Society, an ignorant American public, Bloomberg Green, Bloomberg New Energy Finance, bridge to somewhere, CleanTechnica, control theory, controls theory, decentralized electric power generation, decentralized energy, differential equations, dynamic linear models, dynamical systems, electrical energy engineering, electrical energy storage, electricity, Kalman filter, optimization, photovoltaics, rate of return regulation, solar domination, solar energy, solar revolution, stochastic algorithms, utility company death spiral, wind energy, wind power, zero carbon
Tagged baseload, controls theory, dynamics, electrical engineering, energy storage, marginal cost of energy, solar energy, wind energy
Leave a comment
Phase Plane plots of COVID-19 deaths with uncertainties
I. Introduction. It’s time to fulfill the promise made in “Phase plane plots of COVID-19 deaths“, a blog post from 2nd May 2020, and produce the same with uncertainty clouds about the functional trajectories(*). To begin, here are some assumptions … Continue reading
Posted in American Statistical Association, Andrew Harvey, anomaly detection, count data regression, COVID-19, dependent data, dlm package, Durbin and Koopman, dynamic linear models, epidemiology, filtering, forecasting, Kalman filter, LaTeX, model-free forecasting, Monte Carlo Statistical Methods, numerical algorithms, numerical linear algebra, population biology, population dynamics, prediction, R, R statistical programming language, regression, statistical learning, stochastic algorithms
Tagged prediction intervals
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
“Applications of Deep Learning to ocean data inference and subgrid parameterization”
This is another nail in the coffin of the claim I heard at last year’s Lorenz-Charney Symposium at MIT that machine learning methods would not make a serious contribution to advancements in the geophysical sciences. T. Bolton, L. Zanna, “Applications … Continue reading
Posted in American Meteorological Association, American Statistical Association, artificial intelligence, Azimuth Project, deep learning, deep recurrent neural networks, dynamical systems, geophysics, machine learning, Mathematics and Climate Research Network, National Center for Atmospheric Research, oceanography, oceans, science, stochastic algorithms
Leave a comment
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
Repaired R code for Markov spatial simulation of hurricane tracks from historical trajectories
(Slight update, 28th June 2020.) I’m currently studying random walk and diffusion processes and their connections with random fields. I’m interested in this because at the core of dynamic linear models, Kalman filters, and state-space methods there is a random … Continue reading
Posted in American Meteorological Association, American Statistical Association, AMETSOC, Arthur Charpentier, atmosphere, diffusion, diffusion processes, dynamic linear models, dynamical systems, environment, geophysics, hurricanes, Kalman filter, Kerry Emanuel, Lévy flights, Lorenz, Markov chain random fields, mathematics, mathematics education, maths, MCMC, mesh models, meteorological models, meteorology, model-free forecasting, Monte Carlo Statistical Methods, numerical analysis, numerical software, oceanography, open data, open source scientific software, physics, random walk processes, random walks, science, spatial statistics, state-space models, statistical dependence, statistics, stochastic algorithms, stochastics, time series
1 Comment
A model of an electrical grid: A vision
Many people seem to view the electrical grid of the future being much like the present one. I think a lot about networks, because of my job. And I especially think a lot about network topologies, although primarily concerning the … Continue reading
Posted in abstraction, American Meteorological Association, anomaly detection, Anthropocene, Bloomberg New Energy Finance, BNEF, Boston, bridge to somewhere, Buckminster Fuller, Canettes Blues Band, clean disruption, climate business, climate economics, complex systems, corporate supply chains, decentralized electric power generation, decentralized energy, demand-side solutions, differential equations, distributed generation, efficiency, EIA, electricity, electricity markets, energy, energy reduction, energy storage, energy utilities, engineering, extended supply chains, green tech, grid defection, Hermann Scheer, Hyper Anthropocene, investment in wind and solar energy, ISO-NE, Kalman filter, kriging, Lawrence Berkeley National Laboratory, leaving fossil fuels in the ground, Lenny Smith, local generation, marginal energy sources, Massachusetts Clean Energy Center, Mathematics and Climate Research Network, mesh models, meteorology, microgrids, networks, New England, New York State, open data, organizational failures, pipelines, planning, prediction markets, public utility commissions, PUCs, rate of return regulation, rationality, reason, reasonableness, regime shifts, regulatory capture, resiliency, risk, Sankey diagram, smart data, solar domination, solar energy, solar power, Spaceship Earth, spatial statistics, state-space models, statistical dependence, statistics, stochastic algorithms, stochastics, stranded assets, supply chains, sustainability, the energy of the people, the green century, the value of financial assets, thermodynamics, time series, Tony Seba, utility company death spiral, wave equations, wind energy, wind power, zero carbon
Leave a comment
JASA demands code and data be supplied as a condition of publication
The Journal of the American Statistical Association (“JASA”) has announced in this month’s Amstat News that effective 1st September 2016 “… will require code and data as a minimum standard for reproducibility of statistical scientific research.” Trends were heading this … Continue reading
Posted in American Association for the Advancement of Science, American Statistical Association, citizen science, engineering, ethics, evidence, new forms of scientific peer review, numerical software, planning, rationality, reasonableness, resiliency, science, statistics, stochastic algorithms, testing, the right to know
Leave a comment
France, and Mathematics
Cédric Villani, does Mathematics. “Problems worthy of attack, prove their worth by hitting back.” — Piet Hein
Six cases of models
The previous post included an attempt to explain land surface temperatures as estimated by the BEST project using a dynamic linear model including regressions on both quarterly CO2 concentrations and ocean heat content. The idea was to check the explanatory … Continue reading
Posted in AMETSOC, anemic data, Anthropocene, astrophysics, Bayesian, Berkeley Earth Surface Temperature project, BEST, carbon dioxide, climate, climate change, climate data, climate disruption, climate models, dlm package, dynamic linear models, dynamical systems, environment, fossil fuels, geophysics, Giovanni Petris, global warming, greenhouse gases, Hyper Anthropocene, information theoretic statistics, maths, maximum likelihood, meteorology, model comparison, numerical software, Patrizia Campagnoli, Rauch-Tung-Striebel, Sonia Petrone, state-space models, stochastic algorithms, stochastic search, SVD, time series
1 Comment
“Lucky d20” (by Tamino, with my reblogging comments)
Careful consideration to really basic things like this is, for me, incredibly refreshing, and helps with the self-discipline needed to deal with real-world problems, those often being messy and having distracting entanglements. A couple of thoughts: I think the mechanism … Continue reading
Of my favorite things …
(Clarifying language added 4 Apr 2016, 12:26 EDT.) I just watched an episode from the last season of Star Trek: The Next Generation entitled “Force of Nature.” As anyone who pays the least attention to this blog knows, opposing human … Continue reading
Posted in Anthropocene, bridge to somewhere, bucket list, Buckminster Fuller, Carl Sagan, climate, climate change, climate disruption, climate education, compassion, data science, Earle Wilson, ecology, Ecology Action, environment, evolution, geophysics, George Sughihara, global warming, Hyper Anthropocene, life purpose, mathematics, mathematics education, maths, numerical analysis, optimization, philosophy, physical materialism, physics, population biology, population dynamics, proud dad, quantitative biology, quantitative ecology, rationality, reasonableness, science, sociology, statistics, stochastic algorithms
5 Comments
“Grid shading by simulated annealing” [Martyn Plummer]
Source: Grid shading by simulated annealing (or what I did on my holidays), aka “fun with GCHQ job adverts”, by Martyn Plummer, developer of JAGS. Excerpt: I wanted to solve the puzzle but did not want to sit down with … Continue reading
Posted in approximate Bayesian computation, Bayesian, Bayesian inversion, Boltzmann, BUGS, Christian Robert, Gibbs Sampling, JAGS, likelihood-free, Markov Chain Monte Carlo, Martyn Plummer, mathematics, maths, MCMC, Monte Carlo Statistical Methods, optimization, probabilistic programming, SPSA, stochastic algorithms, stochastic search
Leave a comment
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
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
Leave a comment
Thoughts on “Regime Shift?”
John Baez at The Azimuth Project opened a discussion on the recent paper by Reid, et al Philip C. Reid et al, Global impacts of the 1980s regime shift on the Earth’s climate and systems, Global Change Biology, 2015. I … Continue reading
reblog: “Tiny Data, Approximate Bayesian Computation and the Socks of Karl Broman”
It’s Rasmus Bååth, in a post and video of which I am very fond: http://www.sumsar.net/blog/2014/10/tiny-data-and-the-socks-of-karl-broman/.
What the future of energy everywhere looks like
What will the energy landscape look like after utility companies are either dead, dying, or revert to a tiny portion of their territory? Silicon Valley CCE Partnership gives us all a clue. It’s been described in the San Francisco Chronicle, … Continue reading
Posted in adaptation, Anthropocene, capricious gods, chance, citizenship, civilization, clean disruption, conservation, consumption, decentralized electric power generation, decentralized energy, demand-side solutions, destructive economic development, dynamical systems, economics, efficiency, energy, energy reduction, energy utilities, engineering, environment, ethics, forecasting, fossil fuel divestment, geophysics, global warming, Hyper Anthropocene, investment in wind and solar energy, living shorelines, mesh models, meteorology, microgrids, mitigation, obfuscating data, oceanography, physical materialism, physics, pipelines, planning, politics, prediction, probabilistic programming, public utility commissions, PUCs, quantum, reasonableness, reproducible research, risk, Sankey diagram, science, sea level rise, selfishness, solar energy, solar power, SolarPV.tv, Spaceship Earth, statistics, stochastic algorithms, stochastics, Svante Arrhenius, taxes, temporal myopia, the right to know, the value of financial assets, transparency, UU Humanists, WHOI, wind energy, wind power, zero carbon
Leave a comment
Southern New England Meteorology Conference, 24th October 2015
I attending the 2015 edition of the Southern New England Meteorology Conference in Milton, MA, near the Blue Hill, and its Blue Hill Climatological Observatory, of which I am a member as we as of the American Meteorological Society. I … Continue reading
Posted in Anthropocene, capricious gods, climate, Dan Satterfield, dynamical systems, ensembles, ENSO, environment, floods, forecasting, geophysics, Hyper Anthropocene, information theoretic statistics, mesh models, meteorology, model comparison, NCAR, NOAA, nor'easters, oceanography, probability, science, spatial statistics, state-space models, statistics, stochastic algorithms, stochastic search, stochastics, time series
1 Comment
On differential localization of tumors using relative concentrations of ctDNA. Part 1.
Like most mammalian tissue, tumors often produce shards of DNA as a byproduct of cell death and fracture. This circulating tumor DNA is being studied as a means of detecting tumors or their resurgence after treatment. (See also a Q&A … Continue reading
Posted in approximate Bayesian computation, Bayesian, Bayesian inversion, cardiovascular system, diffusion, dynamic linear models, eigenanalysis, engineering, forecasting, mathematics, maths, medicine, networks, prediction, spatial statistics, statistics, stochastic algorithms, stochastic search, wave equations
3 Comments
On Changing Things
You never change things by fighting the existing reality. To change something, build a new model that makes the existing model obsolete. That’s from Buckminster Fuller, a fellow Unitarian.
Posted in adaptation, Anthropocene, bifurcations, bridge to nowhere, Buckminster Fuller, Cauchy distribution, clean disruption, climate disruption, demand-side solutions, destructive economic development, Disney, dynamic linear models, dynamical systems, Epcot, exponential growth, fossil fuel divestment, global warming, Hyper Anthropocene, physical materialism, planning, rationality, reasonableness, Spaceship Earth, stochastic algorithms
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
“The Bayesian Second Law of Thermodynamics” (Sean Carroll, and collaborators)
http://www.preposterousuniverse.com/blog/2015/08/11/the-bayesian-second-law-of-thermodynamics/ See also.
Posted in approximate Bayesian computation, Bayesian, bifurcations, Boltzmann, capricious gods, dynamical systems, ensembles, games of chance, Gibbs Sampling, information theoretic statistics, Josiah Willard Gibbs, mathematics, maths, physics, probability, rationality, reasonableness, science, statistics, stochastic algorithms, stochastics, thermodynamics, Wordpress
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
“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)
This is a very welcome addition by a master of Bayesian computation, providing a great, brief answer for many of my colleagues who ask, “What’s this MCMC thing about anyway?”
ecoquant
