Distributed Solar: The Democratizaton of Energy
Blogroll
- In Monte Carlo We Trust
- Peter Congdon's Bayesian statistical modeling
- Bob Altemeyer on authoritarianism (via Dan Satterfield)
- Earle Wilson
- Number Cruncher Politics
- distributed solar and matching location to need
- Healthy Home Healthy Planet
- Hermann Scheer
- Charlie Kufs' "Stats With Cats" blog
- Ted Dunning
climate change
- Spectra Energy exposed
- CLIMATE ADAM
- "Betting strategies on fluctuations in the transient response of greenhouse warming"
- Jacobson WWS literature index
- Climate model projections versus observations
- “Ways to [try to] slow the Solar Century''
- Transitioning to fully renewable energy
- Nick Bower's "Scared Scientists"
- Steve Easterbrook's excellent climate blog: See his "The Internet: Saving Civilization or Trashing the Planet?" for example
- `Who to believe on climate change': Simple checks
Archives
Jan Galkowski
Category Archives: Durbin and Koopman
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
ecoquant
