Category Archives: statistical ecology

New Meetup: Massachusetts Mosses and Lichens

I have started a new Meetup group: Massachusetts Mosses and Lichens. I am inviting anyone with an interest in mosses and lichens to join in, particularly if you live in the “greater Massachusetts area”. Because of pandemic, there’ll be no … Continue reading

Posted in ABLS, American Bryological and Lichenological Society, American Statistical Association, biology, Botany, Brent Mishler, bryology, bryophytes, citizen data, citizen science, ecology, field biology, field research, field science, Hale Reservation, Janice Glime, Jerry Jenkins, lichenology, lichens, longitudinal survey of mosses, macrophotography, maths, mesh models, mosses, Nancy G Slack, National Phenology Network, population biology, population dynamics, Ralph Pope, science, spatial statistics, statistical ecology, Sue Williams, the right to know, Westwood | Leave a comment

a song in praise of data scientist Rebekah Jones

I linked to Rebekah Jones‘ keynote address at the August 2020 Data Science Conference on COVID-19 sponsored by the National Institute for Statistical Science. Below is a song in tribute to her, wishing her well. (h/t Bill McKibben) We’re doing … Continue reading

Posted in American Association for the Advancement of Science, American Mathematical Society, American Statistical Association, Boston Ethical Society, children as political casualties, Data for Good, data science, geographic, geographic information systems, International Society for Bayesian Statistics, journalism, mathematics, New England Statistical Society, pandemic, Rebekah Jones, Risky Talk, science, Significance, statistical ecology, statistics, the problem of evil, whistleblowing, ``The tide is risin'/And so are we'' | Leave a comment

What’s wrong with Massachusetts? Land wind turbines!

For groups of people who seriously embrace land wind turbines, there is no downside.

Posted in American Conservation Coalition, American Solar Energy Society, Ørsted, being carbon dioxide, Bloomberg New Energy Finance, bridge to somewhere, Cape Wind, capitalism, CleanTechnica, climate activism, climate disruption, climate policy, Commonwealth of Massachusetts, decentralized electric power generation, decentralized energy, distributed generation, ecocapitalism, ecomodernism, ecopragmatism, education, fossil fuel divestment, global warming, global weirding, Green Tea Coalition, Hermann Scheer, Karl Ragabo, leaving fossil fuels in the ground, local generation, local self reliance, microgrids, mitigating climate disruption, On being Carbon Dioxide, solar democracy, solar domination, solar energy, solar power, solar revolution, Sonnen community, statistical ecology, Talk Solar, the energy of the people, the green century, the tragedy of our present civilization, Tony Seba, tragedy of the horizon, unreason, utility company death spiral, wind energy, wind power, zero carbon | Leave a comment

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

Posted in coronavirus, count data regression, COVID-19, descriptive statistics, epidemiology, pandemic, policy metrics, politics, population biology, population dynamics, quantitative biology, quantitative ecology, sampling, SARS-CoV-2, statistical ecology, statistical series, statistics | 2 Comments

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 | 1 Comment

“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

“Microplastics in the Ocean: Emergency or Exaggeration?” (Morss Colloquium, WHOI)

Update, 2019-10-28 00:34 ET I have compiled notes from the talks above, and from the audience Q&A and documented these in a Google Jam here.

Posted in American Association for the Advancement of Science, bag bans, Claire Galkowski, coastal communities, coasts, diffusion processes, microbiomes, microplastics, NOAA, oceanic eddies, oceanography, oceans, perceptions, phytoplankton, plastics, pollution, quantitative biology, quantitative ecology, science, science education, statistical ecology, WHOI, Woods Hole Oceanographic Institution | Leave a comment

cdetools package for R: Dalmasso, et al [updated]

Just hit the “arXiv streets”: N. Dalmasso, T. Pospisil, A. B. Lee, R. Izbicki, P. E. Freeman, A. I. Malz, “Conditional Density Estimation Tools in Python and R with applications to photometric redshifts and likelihood-free cosmological inference”, > astro-ph … Continue reading

Posted in ABC, accept-reject methods, astronomy, astrophysics, astrostatistics, Bayes, Bayesian computational methods, likelihood-free, statistical ecology | Leave a comment