Category Archives: Floris Takens

Liang, information flows, causation, and convergent cross-mapping

Someone recommended the work of Liang recently in connection with causation and attribution studies, and their application to CO2 and climate change. Liang’s work is related to information flows and transfer entropies. As far as I know, the definitive work … Continue reading

Posted in Akaike Information Criterion, American Association for the Advancement of Science, Anthropocene, attribution, carbon dioxide, climate, climate change, climate disruption, complex systems, convergent cross-mapping, ecology, Egbert van Nes, Ethan Deyle, Floris Takens, George Sughihara, global warming, Hao Ye, Hyper Anthropocene, information theoretic statistics, Lenny Smith, model-free forecasting, nonlinear systems, physics, statistics, Takens embedding theorem, theoretical physics, Timothy Lenton, Victor Brovkin | Leave a comment

“Stochastic Parameterization: Towards a new view of weather and climate models”

Judith Berner, Ulrich Achatz, Lauriane Batté, Lisa Bengtsson, Alvaro De La Cámara, Hannah M. Christensen, Matteo Colangeli, Danielle R. B. Coleman, Daan Crommelin, Stamen I. Dolaptchiev, Christian L.E. Franzke, Petra Friederichs, Peter Imkeller, Heikki Järvinen, Stephan Juricke, Vassili Kitsios, François … Continue reading

Posted in biology, climate models, complex systems, convergent cross-mapping, data science, dynamical systems, ecology, Ethan Deyle, Floris Takens, George Sughihara, Hao Ye, likelihood-free, Lorenz, mathematics, meteorological models, model-free forecasting, physics, population biology, population dynamics, quantitative biology, quantitative ecology, Scripps Institution of Oceanography, state-space models, statistical dependence, statistics, stochastic algorithms, stochastic search, stochastics, Takens embedding theorem, time series, Victor Brovkin | 4 Comments

“Causal feedbacks in climate change”

Today I was reviewing and re-reading the nonlinear time series technical literature I have, seeking ideas on how to go about using the statistical ensemble learning technique called “boosting” with them. (See the very nice book, R. E. Schapire, Y. … Continue reading

Posted in Anthropocene, boosting, Carbon Cycle, carbon dioxide, Carbon Worshipers, cat1, climate, climate change, climate data, climate disruption, complex systems, convergent cross-mapping, denial, differential equations, diffusion processes, dynamical systems, ecology, Egbert van Nes, empirical likelihood, ensembles, environment, Ethan Deyle, Floris Takens, forecasting, fossil fuels, geophysics, George Sughihara, global warming, greenhouse gases, Hao Ye, machine learning, Maren Scheffer, mathematics, maths, meteorology, physics, rationality, reasonableness, science, state-space models, Takens embedding theorem, time series, Timothy Lenton, Victor Brovkin | 2 Comments

All I do is complain, complain …

I was reviewing a presentation given as part of a short course in the machine learning genre today, and happened across the following two bullets, under the heading “Strictly Stationary Processes”: Predicting a time series is possible if and only … Continue reading

Posted in bifurcations, chaos, citizen science, convergent cross-mapping, dynamic linear models, dynamical systems, engineering, Floris Takens, generalized linear models, geophysics, George Sughihara, ignorance, Lenny Smith, Lorenz, mathematics, maths, meteorology, prediction, probability, rationality, reasonableness, statistics, stochastic algorithms, stochastic search, stochastics, Takens embedding theorem, the right to know, time series | 1 Comment