### Distributed Solar: The Democratizaton of Energy

### Blogroll

- Label Noise
- Healthy Home Healthy Planet
- Dollars per BBL: Energy in Transition
- Giant vertical monopolies for energy have stopped making sense
- Gavin Simpson
- Dominic Cummings blog
- "Perpetual Ocean" from NASA GSFC
- Los Alamos Center for Bayesian Methods
- Logistic curves in market disruption
- Subsidies for wind and solar versus subsidies for fossil fuels

### climate change

- David Appell's early climate science
- James Hansen and granddaughter Sophie on moving forward with progress on climate
- Model state level energy policy for New Englad
- Spectra Energy exposed
- The HUMAN-caused greenhouse effect, in under 5 minutes, by Bill Nye
- Climate Communication
- Andy Zucker's "Climate Change and Psychology"
- “The discovery of global warming'' (American Institute of Physics)
- ATTP summarizes all that stuff about Committed Warming
- Tell Utilities Solar Won't Be Killed

### Archives

### Jan Galkowski

# Tag Archives: prediction intervals

## 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