Distributed Solar: The Democratizaton of Energy
Category Archives: statistics
What happens when time sampling density of a series matches its growth
This is the newly updated map of COVID-19 cases in the United States, updated, presumably, because of the new emphasis upon testing: How do we know this is the recent of recent testing? Look at the map of active cases: … Continue reading
Posted in American Association for the Advancement of Science, American Statistical Association, anti-intellectualism, anti-science, climate denial, corruption, data science, data visualization, Donald Trump, dump Trump, epidemiology, experimental science, exponential growth, forecasting, Kalman filter, model-free forecasting, nonlinear systems, open data, penalized spline regression, population dynamics, sampling algorithms, statistical ecology, statistical models, statistical regression, statistical series, statistics, sustainability, the right to know, the stack of lies
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“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.
Reanalysis of business visits from deployments of a mobile phone app
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 of the American Statistical … 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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There’s Big Data, Tiny Data, and now Dead Data
You’ve heard of Big Data. You may have heard of Tiny Data. But now, presented in the Harvard Data Science Review, Professor Steve Stigler presents Dead Data See: S. M. Stigler, “Data have a limited shelf life”, Harvard Data Science … Continue reading
Posted in big data, dead data, statistics, tiny data
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“Tensors in Algebraic Statistics” (Elizabeth Gross)
Professor Elizabeth Gross. Some notes: Segre variety, about (These will be updated as I make progress through the talk.)
Posted in statistics, tensors
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Review of “No … increase of Carbon sequestration from the greening Earth”
(As promised.) Introduction and Abstract This is a review, re-presentation, and report on the August 2019 article, Y. Zhang, C. Song, L. E. Band, G. Sun, (2019), “No proportional increase of terrestrial gross Carbon sequestration from the greening Earth“, Journal … Continue reading
Posted in adaptation, afforestation, agriculture, agroecology, algal blooms, American Statistical Association, argoecology, being carbon dioxide, biology, Botany, bridge to somewhere, carbon dioxide, carbon dioxide sequestration, chemistry, citizen science, clear air capture of carbon dioxide, climate, climate data, climate disruption, climate economics, climate mitigation, di-nitrogen oxide, ecocapitalism, ecological disruption, Ecological Society of America, ecomodernism, ecopragmatism, environment, evidence, food, forests, fossil fuels, geophysics, Glen Peters, Global Carbon Project, greenhouse gases, James Hansen, John Holdren, p-value, phytoplankton, pollution, population biology, quantitative biology, resource producitivity, scholarship, science education, significance test, statistics, Steven Chu, sustainability, sustainable landscaping, wishful environmentalism
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“Bayesian replication analysis” (by John Kruschke)
“… the ability to express [hypotheses] as distributions over parameters …” Bayesian estimation supersedes the t-test: (Also by Professor Kruschke.)
“Ten Fatal Flaws in Data Analysis” (Charles Kufs)
Professor Kufs has a fun book, Stats with Cats, and a blog. He also has a blog post tiled “Ten Fatal Flaws in Data Analysis” which, in general, I like. But the presentation has some shortcomings, too, which I note … Continue reading
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
What’s good for each subgroup can be bad for the group: Simpson’s
Why? Simpson’s “paradox” or observation … There’s actually nothing odd about this. While interpretation depends upon the semantics of individual measurements, it should be expected that, at times, improving things for the overall group will mean as a matter of … Continue reading
Posted in abstraction, statistics
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California Marine Debris Prevention: Banning Plastic Bags is Not Enough
NOAA has a full page of videos on marine debris and how to prevent it. The state of California has a 2018 plan on preventing marine debris. Here are some highlights. There is a good deal more in the report, … Continue reading
Posted in American Statistical Association, Life Cycle Assessment, life cycle sustainability analysis, policy metrics, public welfare, shop, shorelines, solid waste, solid waste management, South Shore Recycling Cooperative, spatial statistics, statistical series, statistics, supply chains, sustainability, the right to know, wishful environmentalism
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Five Thirty Eight podcast: `Can Statistics solve gerrymandering?`
Great podcast, featuring Professor and geometer Moon Duchin, Nate Silver, and Galen Druke. If the link doesn’t work, listen from here or below: Professor Duchin has written extensively on this: M. Duchin, B. E. Tenner, “Discrete geometry for electoral geography”, … Continue reading
On bag bans and sampling plans
Plastic bag bans are all the rage. It’s not the purpose of this post to take a position on the matter. Before you do, however, I’d recommend checking out this: and especially this: (Note: My lovely wife, Claire, presents this … Continue reading
Posted in bag bans, citizen data, citizen science, Commonwealth of Massachusetts, Ecology Action, evidence, Google, Google Earth, Google Maps, goverance, lifestyle changes, microplastics, municipal solid waste, oceans, open data, planning, plastics, politics, pollution, public health, quantitative ecology, R, R statistical programming language, reasonableness, recycling, rhetorical statistics, sampling, sampling networks, statistics, surveys, sustainability
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Repeating Bullshit
Originally posted on Open Mind:
Question: How does a dumb claim go from just a dumb claim, to accepted canon by the climate change denialati? Answer: Repetition. Yes, keep repeating it. If it’s contradicted by evidence, ignore that or insult…
A look at an electricity consumption series using SNCDs for clustering
(Slightly amended with code and data link, 12th January 2019.) Prediction of electrical load demand or, in other words, electrical energy consumption is important for the proper operation of electrical grids, at all scales. RTOs and ISOs forecast demand based … Continue reading
Posted in American Statistical Association, consumption, data streams, decentralized electric power generation, dendrogram, divergence measures, efficiency, electricity, electricity markets, energy efficiency, energy utilities, ensembles, evidence, forecasting, grid defection, hierarchical clustering, hydrology, ILSR, information theoretic statistics, local self reliance, Massachusetts, microgrids, NCD, normalized compression divergence, numerical software, open data, prediction, rate of return regulation, Sankey diagram, SNCD, statistical dependence, statistical series, statistics, sustainability, symmetric normalized compression divergence, time series
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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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Why Americans and Britons work such long hours
Why Americans and Britons work such long hours.
Posted in business, economics, labor, statistics
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667-per-cm.net, the Podcast: Episode 2, or Probability is Real.
This is the second installment of the Podcast here, hopefully with better sound quality.
Posted in probability, random walks, statistics
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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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“All of Monsanto’s problems just landed on Bayer” (by Chris Hughes at Bloomberg)
See Chris Hughes’ article. Monsanto has touted Roundup (also known as Glyphosate but more properly as ) as a safe remedy for weed control, often in the taming of so-called “invasive species”. It’s used on playfields where children are exposed … Continue reading
Posted in agroecology, an uncaring American public, business, corporate responsibility, ecology, Ecology Action, environment, environmental law, epidemiology, evidence, invasive species, open data, Peter del Tredici, quantitative biology, quantitative ecology, rights of the inhabitants of the Commonwealth, risk, statistics, sustainability, sustainable landscaping, the right to know, Uncategorized, unreason, Westwood
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Less evidence for a global warming hiatus, and urging more use of Bayesian model averaging in climate science
(This post has been significantly updated midday 15th February 2018.) I’ve written about the supposed global warming hiatus of 2001-2014 before: “‘Overestimated global warming over the past 20 years’ (Fyfe, Gillett, Zwiers, 2013)”, 28 August 2013 “Warming Slowdown?”, Azimuth, Part … Continue reading
Posted in American Statistical Association, Andrew Parnell, anomaly detection, Anthropocene, Bayesian, Bayesian model averaging, Berkeley Earth Surface Temperature project, BEST, climate change, David Spiegelhalter, dependent data, Dublin, GISTEMP, global warming, Grant Foster, HadCRUT4, hiatus, Hyper Anthropocene, JAGS, Markov Chain Monte Carlo, Martyn Plummer, Mathematics and Climate Research Network, MCMC, model-free forecasting, Niamh Cahill, Significance, statistics, Stefan Rahmstorf, Tamino
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Senn’s `… never having to say you are certain’ guest post from Mayo’s blog
via S. Senn: Being a statistician means never having to say you are certain (Guest Post) See also: E. Cai’s blog post “Applied Statistics Lesson of the Day – The Matched Pairs Experimental Design”, from February 2014 A. Deaton, N. … Continue reading
Posted in abstraction, American Association for the Advancement of Science, American Statistical Association, cancer research, data science, ecology, experimental design, generalized linear mixed models, generalized linear models, Mathematics and Climate Research Network, medicine, sampling, statistics, the right to know
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(thought of the day)
One accurate measurement is worth a thousand expert opinions. — Grace Murray Hopper Hat tip to Pat’s blog.
Posted in statistics, Uncategorized
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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
What are the odds of net zero?
What’s the Question? A question was posed by a colleague a couple of months ago: What are the odds of a stock closing at the same price it opened? I found the question interesting, because, at first, it appeared to … Continue reading
From Xian’s blog, “drivers are not interested in maths formulas”
via drivers are not interested in maths formulas
Confidence intervals and that IPCC: Why climate scientists need statistical help
At Andrew Gelman’s blog (Statistical Modeling, Causal Inference, and Social Science), Ben Goodrich makes the interesting observation in a length discussion about confidence intervals, how they should be interpreted, whether or not they have any socially redeeming value, und so … Continue reading
Posted in Bayesian, climate, IPCC, statistics
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