Distributed Solar: The Democratizaton of Energy
Blogroll
- Ives and Dakos techniques for regime changes in series
- All about Sankey diagrams
- Quotes by Nikola Tesla
- The Plastic Pick-Up: Discovering new sources of marine plastic pollution
- Higgs from AIR describing NAO and EA
- The Keeling Curve: its history
- Professor David Draper
- Team Andrew Weinberg
- Charlie Kufs' "Stats With Cats" blog
- Giant vertical monopolies for energy have stopped making sense
climate change
- The Carbon Cycle
- NOAA Annual Greenhouse Gas Index report
- Climate Change Reports
- "A field guide to the climate clowns"
- Updating the Climate Science: What path is the real world following?
- Professor Robert Strom's compendium of resources on climate change
- Agendaists
- The Scientific Case for Modern Human-caused Global Warming
- SolarLove
- ATTP summarizes all that stuff about Committed Warming
Archives
Jan Galkowski
Category Archives: epidemiology
ICL’s Gast, Openshaw, Riley, Barclay on COVID-19 by SARS-CoV-2 : Disease, transmission, variants, and all that
Posted in COVID-19, epidemiology, ICL, SARS-CoV-2
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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
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“No, COVID-19 Is not the Flu”
Q&A with Andrew Pekosz, PhD, Johns Hopkins University: Q: What would you say to someone who insists to you that COVID-19 is “just the flu”? A: Since December 2019, COVID-19 has killed more people in the U.S. than influenza has … Continue reading
Posted in coronavirus, COVID-19, epidemiology, SARS-CoV-2
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Rebekah Jones
From Rebekah Jones‘ keynote at the Data Science for COVID-19: Florida COVID Action The COVID Monitor Google COVID-19 Open Data Project
Posted in epidemiology, ethical ideals, ethics, Rebekah Jones, whistleblowing
Tagged Florida COVID Action, The COVID Monitor
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Has maintaining economic growth been worth it?
From Our World in Data article “No sign of a health-economy trade-off, quite the opposite“. Have the countries experiencing the largest economic decline performed better in protecting the nation’s health, as we would expect if there was a trade-off? The … Continue reading
Posted in coronavirus, COVID-19, economics, epidemiology, pandemic, policy metrics, politics, SARS-CoV-2
Tagged covid19, economicimpact, lives_for_dollars, pandemicresponse, sars_cov_2
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“Inferring change points in the spread of COVID-19 reveals the effectiveness of interventions”
J. Dehning et al., Science 369, eabb9789 (2020). DOI: 10.1126/science.abb9789 Source code and data. Note: This is not a classical approach to assessing strength of interventions using either counterfactuals or other kinds of causal inference. Accordingly, the argument for the … Continue reading
Posted in American Association for the Advancement of Science, American Statistical Association, Bayesian, Bayesian computational methods, causal inference, causation, changepoint detection, coronavirus, counterfactuals, COVID-19, epidemiology, SARS-CoV-2, state-space models, statistical series, time series
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COVID-19 statistics, a caveat : Sources of data matter
There are a number of sources of COVID-19-related demographics, cases, deaths, numbers testing positive, numbers recovered, and numbers testing negative available. Many of these are not consistent with one another. One could hope at least rates would be consistent, but … Continue reading
First substantial mechanism for long term immunity from SARS-CoV-2 : T-cells
M. Leslie, “T cells found in COVID-19 patients ‘bode well’ for long-term immunity“, Science, doi:10.1126/science.abc8120. A. Grifoni, et al, “Targets of T cell responses to SARS-CoV-2 coronavirus in humans with COVID-19 disease and unexposed individuals“, Cell, 14th May 2020. J. … Continue reading
“Seasonality of COVID-19, Other Coronaviruses, and Influenza” (from Radford Neal’s blog)
Thorough review with documentation and technical criticism of claims of COVID-19 seasonality or its lack. Whichever way this comes down, the links are well worth the visit! Will the incidence of COVID-19 decrease in the summer? There is reason to … Continue reading
New COVID-19 incidence in the United States as AR(1) processes
There are several sources of information regarding Covid-19 incidence now available. This post uses data from a single source: the COVID Tracking Project. In particular I restrict attention to cumulative daily case counts for the United States, the UK, and … Continue reading
Posted in coronavirus, COVID-19, epidemiology, pandemic, regression, SARS-CoV-2
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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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R ecosystem package coronavirus
Dr Rami Krispin of the Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) has just released the R package coronavirus, which “provides a daily summary of the Coronavirus (COVID-19) cases by state/province“, caused by 2019-nCoV. (update 2020-03-12 … Continue reading
Posted in data presentation, data science, epidemiology
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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.
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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Censorship of Science by the administration of President Donald Trump
See work by the Columbia Sabin Center for Climate Change Law. … President Trump has directed EPA and DOI to reconsider regulations adopted to control greenhouse gas emissions, despite the wealth of data showing that those emissions are the key … Continue reading
Posted in American Association for the Advancement of Science, an ignorant American public, an uncaring American public, anti-intellectualism, anti-science, Azimuth Backup Project, citizen data, Climate Science Legal Defense Fund, Donald Trump, dump Trump, Ecological Society of America, environmental law, epidemiology, global blinding, Neill deGrasse Tyson, open data, rationality, reason, reasonableness, science, secularism, The Demon Haunted World, the right to be and act stupid, the right to know, the tragedy of our present civilization, tragedy of the horizon, unreason
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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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“Will climate change bring benefits from reduced cold-related mortality? Insights from the latest epidemiological research”
From RealClimate, and referring to article in Lancet : Guest post by Veronika Huber Climate skeptics sometimes like to claim that although global warming will lead to more deaths from heat, it will overall save lives due to fewer deaths from … Continue reading