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On Sampling and Modeling Complex Systems

Published on Dec 04, 20131858 Views

The study of complex systems is limited by the fact that only few variables are accessible for modeling and sampling, which are not necessarily the most relevant ones to explain the systems behavior.

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Chapter list

On Sampling and Modeling Complex Systems00:00
Science is a miracle00:24
Facts and more questions03:37
Criticality: Zipf’s law05:52
Criticality in economics and the brain07:58
The only things all these phenomena have in common09:03
E.g. language: an efficient way to say complex things09:30
Why do you live where you live?12:50
Complex system = many degrees of freedom + function14:36
Key issue: what variables do we look at?16:02
Modeling: (the direct problem)17:40
Sampling: (the inverse problem)23:03
Where is the information in the sample?24:19
How much information?26:19
Maximally informative samples (upper bound)31:10
Applications/examples32:26
Subsampling city distribution33:30
Finding relevant variables 1: Classifying 4000 NYSE stocks33:40
H[K] can be used to score clustering methods35:41
Finding relevant variables 2: Keywords in text37:42
The Origin of the Species38:25
Finding relevant variables 3: Choosing relevant positions in proteins39:00
Conserved variables are not the only relevant relevant ones40:23
Optimal sampling and experiment design41:07
Summary41:15
A numerical recipe42:14