Interpreting the Ising Model: The Input Matters
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The Ising model is a model for pairwise interactions between binary variables that has become popular in the psychological sciences as discussed by the authors, and it has been first introduced as a theoretical model for the alig...Abstract:
The Ising model is a model for pairwise interactions between binary variables that has become popular in the psychological sciences. It has been first introduced as a theoretical model for the alig...read more
Citations
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Modeling Psychopathology: From Data Models to Formal Theories
TL;DR: This dissertation deals with the problem of modeling psychopathology and introduces a number of models for cross-sectional and time series data that can be visualized as a network and puts forward an abductive framework for constructing formal theories for psychological and psychopathological phenomena.
Journal ArticleDOI
Personality, Resilience, and Psychopathology: A Model for the Interaction between Slow and Fast Network Processes in the Context of Mental Health
TL;DR: Network theories have been put forward for psychopathology (in which mental disorders originate from causal relations between symptoms) and personality factors as mentioned in this paper, in which personality factors originate from personality factors.
Posted ContentDOI
Intervening on psychopathology networks: Evaluating intervention targets through simulations.
TL;DR: The NodeIdentifyR algorithm (NIRA) as discussed by the authors was proposed to identify the projected most efficient, symptom-specific intervention target in a network model (i.e., the Ising model).
Journal ArticleDOI
Intervening on psychopathology networks: Evaluating intervention targets through simulations
TL;DR: The NodeIdentifyR algorithm (NIRA) as mentioned in this paper was proposed to identify the projected most efficient, symptom-specific intervention target in a network model (i.e., the Ising model).
Journal ArticleDOI
The Mental Health Ecosystem: Extending Symptom Networks With Risk and Protective Factors.
Gabriela Lunansky,Claudia D. van Borkulo,Jonas M. B. Haslbeck,Max A. van der Linden,Cristian Javier Garay,Martín Etchevers,Denny Borsboom +6 more
TL;DR: In this article, the authors investigate the multifactorial nature of resilience and present a system in which a network of interacting psychiatric symptoms is targeted by risk and protective factors to increase or decrease the probability that the symptom network is pulled towards a healthy or disorder state.
References
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Estimating the Dimension of a Model
TL;DR: In this paper, the problem of selecting one of a number of models of different dimensions is treated by finding its Bayes solution, and evaluating the leading terms of its asymptotic expansion.
Estimating the dimension of a model
TL;DR: In this paper, the problem of selecting one of a number of models of different dimensions is treated by finding its Bayes solution, and evaluating the leading terms of its asymptotic expansion.
Book
Graphical Models, Exponential Families, and Variational Inference
TL;DR: The variational approach provides a complementary alternative to Markov chain Monte Carlo as a general source of approximation methods for inference in large-scale statistical models.
Journal ArticleDOI
Time‐Dependent Statistics of the Ising Model
TL;DR: In this paper, the effect of a uniform, time-varying magnetic field upon the Ising model is discussed, and the frequency-dependent magnetic susceptibility is found in the weak-field limit.