Complexity, chaos and catastrophe Modeling psychopathology as a dynamic system
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| Publication date | 2020 |
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| Book title | Network Science in Cognitive Psychology |
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| Series | Frontiers of Cognitive Psychology |
| Chapter | 3 |
| Pages (from-to) | 45-79 |
| Publisher | New York: Routledge |
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| Abstract |
In recent years, the notion that correlations between questionnaire items are the result of direct interactions between these variables has grown in popularity. Various methods exist for estimating the connectivity of a network. Networks can be estimated for an entire group or for individuals. All three methods control for such potentially spurious edges by using the least absolute shrinkage and selection operator. Essentially, the IsingFit method regresses one node on all other nodes in an iterative manner, using the optimal penalty parameter. Both networks are equally important and interesting: when collecting time-series data, one is often interested in the progression of an individual throughout time. There is evidence for the hypothesis that all catastrophic systems, from financial systems to the climate, display early warning signals that the system is approaching a tipping point. The empirical mean field approximation is based on the work of Waldorp and Kossakowski..
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| Document type | Chapter |
| Language | English |
| Published at | https://doi.org/10.4324/9780367853259-4 |
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