### Distributed Solar: The Democratizaton of Energy

### Blogroll

- "Impacts of Green New Deal energy plans on grid stability, costs, jobs, health, and climate in 143 countries" (Jacobson, Delucchi, Cameron, et al)
- Carl Safina's blog
- Risk and Well-Being
- Pat's blog
- Mike Bloomberg, 2020
- Beautiful Weeds of New York City
- All about Sankey diagrams
- Why It’s So Freaking Hard To Make A Good COVID-19 Model
- Number Cruncher Politics
- Ives and Dakos techniques for regime changes in series

### climate change

- HotWhopper: It's excellent.
- The Scientific Case for Modern Human-caused Global Warming
- Climate at a glance
- Earth System Models
- Grid parity map for Solar PV in United States
- James Hansen and granddaughter Sophie on moving forward with progress on climate
- Climate model projections versus observations
- Transitioning to fully renewable energy
- Agendaists
- All Models Are Wrong

### Archives

### Jan Galkowski

# Category Archives: logistic regression

## Newt Gingrich and Van Jones. Right on.

It’s the thing. And it addresses how media and people forget about the actual statistics, and focus on the White Hot Bright Light. A study by Gelman, Fagan, and Kiss A study by Freyer A counterpoint to the Freyer study … Continue reading

Posted in American Statistical Association, Bayes, Bayesian, citizen science, criminal justice, Daniel Kahneman, ethics, evidence, fear uncertainty and doubt, humanism, Lives Matter, logistic regression, Markov Chain Monte Carlo, MCMC, organizational failures, population biology, rationality, reasonableness, risk, statistics, Susan Jacoby, the right to know
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## On Smart Data

One of the things I find surprising, if not astonishing, is that in the rush to embrace Big Data, a lot of learning and statistical technique has been left apparently discarded along the way. I’m hardly the first to point … Continue reading

Posted in Akaike Information Criterion, Bayes, Bayesian, Bayesian inversion, big data, bigmemory package for R, changepoint detection, data science, data streams, dlm package, dynamic generalized linear models, dynamic linear models, dynamical systems, Generalize Additive Models, generalized linear models, information theoretic statistics, Kalman filter, linear algebra, logistic regression, machine learning, Markov Chain Monte Carlo, mathematics, mathematics education, maths, maximum likelihood, MCMC, Monte Carlo Statistical Methods, multivariate statistics, numerical analysis, numerical software, numerics, quantitative biology, quantitative ecology, rationality, reasonableness, sampling, smart data, state-space models, statistical dependence, statistics, the right to know, time series
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## Markov Chain Monte Carlo methods and logistic regression

This post could also be subtitled “Residual deviance isn’t the whole story.” My favorite book on logistic regression is by Dr Joseph Hilbe, Logistic Regression Models, CRC Press, 2009, Chapman & Hill. It is a solidly frequentist text, but its … Continue reading

Posted in Bayes, Bayesian, logistic regression, MCMC, notes, R, statistics, stochastic algorithms, stochastic search
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