Distributed Solar: The Democratizaton of Energy
Blogroll
- Fear and Loathing in Data Science
- Karl Broman
- "Perpetual Ocean" from NASA GSFC
- American Association for the Advancement of Science (AAAS)
- Why It’s So Freaking Hard To Make A Good COVID-19 Model
- Earle Wilson
- Ives and Dakos techniques for regime changes in series
- American Statistical Association
- Darren Wilkinson's introduction to ABC
- Team Andrew Weinberg
climate change
Archives
Category Archives: linear algebra
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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On differential localization of tumors using relative concentrations of ctDNA. Part 2.
Part 1 of this series introduced the idea of ctDNA and its use for detecting cancers or their resurgence, and proposed a scheme whereby relative concentrations of ctDNA at two or more sites after controlled disturbance might be used to … Continue reading