Distributed Solar: The Democratizaton of Energy
Blogroll
- AP Statistics: Sampling, by Michael Porinchak
- Tim Harford's “More or Less''
- Hermann Scheer
- The Plastic Pick-Up: Discovering new sources of marine plastic pollution
- Karl Broman
- John Cook's reasons to use Bayesian inference
- Professor David Draper
- Ives and Dakos techniques for regime changes in series
- "Talking Politics" podcast
- All about Sankey diagrams
climate change
- Professor Robert Strom's compendium of resources on climate change
- Earth System Models
- AIP's history of global warming science: impacts
- Skeptical Science
- "A field guide to the climate clowns"
- Dessler's 6 minute Greenhouse Effect video
- Climate Change: A health emergency … New England Journal of Medicine
- On Thomas Edison and Solar Electric Power
- Energy payback period for solar panels
- The great Michael Osborne's latest opinions
Archives
Category Archives: astrostatistics
Happy Newtonmas, 2020
Among other projects I support this year, post-retirement is Einstein@Home Why? Because with all the emphasis upon SARS-CoV-2, biopharmaceuticals, and mitigating climate disruption, which are all important, observational astronomy doesn’t get enough love. And this is an astronomy which isn’t … Continue reading
Posted in astronomy, astrostatistics, BOINC, Einstein@Home, physics
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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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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”, arXiv.org > astro-ph … Continue reading