### Distributed Solar: The Democratizaton of Energy

### Blogroll

- London Review of Books
- Dollars per BBL: Energy in Transition
- John Cook's reasons to use Bayesian inference
- Darren Wilkinson's introduction to ABC
- The Mermaid's Tale
- Musings on Quantitative Paleoecology
- GeoEnergy Math
- Bob Altemeyer on authoritarianism (via Dan Satterfield)
- Higgs from AIR describing NAO and EA
- John Kruschke's "Dong Bayesian data analysis" blog

### climate change

- Simple box models and climate forcing
- Andy Zucker's "Climate Change and Psychology"
- Updating the Climate Science: What path is the real world following?
- Simple models of climate change
- "Warming Slowdown?" (part 2 of 2)
- An open letter to Steve Levitt
- James Hansen and granddaughter Sophie on moving forward with progress on climate
- All Models Are Wrong
- "Lessons of the Little Ice Age" (Farber)
- Documenting the Climate Deniarati at work

### Archives

### Jan Galkowski

# Category Archives: Rauch-Tung-Striebel

## Six cases of models

The previous post included an attempt to explain land surface temperatures as estimated by the BEST project using a dynamic linear model including regressions on both quarterly CO2 concentrations and ocean heat content. The idea was to check the explanatory … Continue reading

Posted in AMETSOC, anemic data, Anthropocene, astrophysics, Bayesian, Berkeley Earth Surface Temperature project, BEST, carbon dioxide, climate, climate change, climate data, climate disruption, climate models, dlm package, dynamic linear models, dynamical systems, environment, fossil fuels, geophysics, Giovanni Petris, global warming, greenhouse gases, Hyper Anthropocene, information theoretic statistics, maths, maximum likelihood, meteorology, model comparison, numerical software, Patrizia Campagnoli, Rauch-Tung-Striebel, Sonia Petrone, state-space models, stochastic algorithms, stochastic search, SVD, time series
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## Cory Lesmeister’s treatment of Simson’s Paradox (at “Fear and Loathing in Data Science”)

(Updated 2016-05-08, to provide reference for plateaus of ML functions in vicinity of MLE.) Simpson’s Paradox is one of those phenomena of data which really give Statistics a substance and a role, beyond the roles it inherits from, say, theoretical … Continue reading

Posted in Akaike Information Criterion, approximate Bayesian computation, Bayes, Bayesian, evidence, Frequentist, games of chance, information theoretic statistics, Kalman filter, likelihood-free, mathematics, maths, maximum likelihood, Monte Carlo Statistical Methods, probabilistic programming, rationality, Rauch-Tung-Striebel, Simpson's Paradox, state-space models, statistical dependence, statistics, stochastics
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## Thoughts on “Regime Shift?”

John Baez at The Azimuth Project opened a discussion on the recent paper by Reid, et al Philip C. Reid et al, Global impacts of the 1980s regime shift on the Earth’s climate and systems, Global Change Biology, 2015. I … Continue reading

## Comprehensive and compact tutorial on Petris’ DLM package in R; with an update about Helske’s KFAS

A blogger named Lalas produced on Quantitative Thoughts a very comprehensive and compact tutorial on the R package dlm by Petris. I use dlm a lot. Unfortunately, Lalas does not give details on how the SVD is used. They do … Continue reading

Posted in Bayes, Bayesian, dynamic linear models, dynamical systems, forecasting, Kalman filter, mathematics, maths, multivariate statistics, numerical software, open source scientific software, prediction, R, Rauch-Tung-Striebel, state-space models, statistics, stochastic algorithms, SVD, time series
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