Distributed Solar: The Democratizaton of Energy
Blogroll
- Peter Congdon's Bayesian statistical modeling
- BioPython
- WEAPONS OF MATH DESTRUCTION, reviews
- Brendon Brewer on Overfitting
- "Consider a Flat Pond"
- The Mermaid's Tale
- Why "naive Bayes" is not Bayesian
- Patagonia founder Yvon Chouinard on how businesses can help our collective environmental mess
- Beautiful Weeds of New York City
- Harvard's Project Implicit
climate change
- Paul Beckwith
- Model state level energy policy for New Englad
- Rabett Run
- Updating the Climate Science: What path is the real world following?
- Wally Broecker on climate realism
- The HUMAN-caused greenhouse effect, in under 5 minutes, by Bill Nye
- Energy payback period for solar panels
- Social Cost of Carbon
- And Then There's Physics
- "Getting to the Energy Future We Want," Dr Steven Chu
Archives
Jan Galkowski
Category Archives: Jerome Friedman
high dimension Metropolis-Hastings algorithms
If attempting to simulate from a multivariate standard normal distribution in a large dimension, when starting from the mode of the target, i.e., its mean γ, leaving the mode γis extremely unlikely, given the huge drop between the value of the density at the mode γ and at likely realisations Continue reading
Posted in Bayes, Bayesian, Bayesian inversion, boosting, chance, Christian Robert, computation, ensembles, Gibbs Sampling, James Spall, Jerome Friedman, Markov Chain Monte Carlo, mathematics, maths, MCMC, Monte Carlo Statistical Methods, multivariate statistics, numerical software, numerics, optimization, reasonableness, Robert Schapire, SPSA, state-space models, statistics, stochastic algorithms, stochastic search, stochastics, Yoav Freund
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