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Identifying dynamic spillovers of crime with a causal approach to model selection

Gregorio Caetano, Vikram Maheshri
2018 Quantitative Economics  
model for causal inference.  ...  Using a detailed incident-based data set of all reported crimes in Dallas from 2000 to 2007, we find some evidence of dynamic spillovers within certain types of crimes, but no evidence that lighter crimes  ...  Conclusion Researchers typically approach causal inference problems with a source of variation that is already known to be "as good as random."  ... 
doi:10.3982/qe756 fatcat:lrsdc3pz2fdapiiocmzaka43p4

On the Incompatibility of Dynamical Biological Mechanisms and Causal Graphs

Marcel Weber
2016 Philosophy of Science  
A formal mechanistic model will therefore either have to leave out non-causal or causal explanatory relations.  ...  Thus, in principle it is possible to integrate causal difference-making information with dynamical information.  ...  Acknowledgements I wish to thank in particular Marie Kaiser, Lorenzo Casini, Alexander Gebharter, Naftali Weinberger, the audience at the PSA 2014 symposium "How Adequate Are Causal Graphs and Bayesian  ... 
doi:10.1086/687878 fatcat:m6dtpvhobzciffhgvlihczgtia

Participatory Problem Formulation for Fairer Machine Learning Through Community Based System Dynamics [article]

Donald Martin Jr.
2020 arXiv   pre-print
In this paper we introduce community based system dynamics (CBSD) as an approach to enable the participation of typically excluded stakeholders in the problem formulation phase of the ML system development  ...  Recent research on algorithmic fairness has highlighted that the problem formulation phase of ML system development can be a key source of bias that has significant downstream impacts on ML system fairness  ...  ACKNOWLEDGMENTS We would like to thank Emily Denton, Ben Hutchinson, Sean Legassick, Silvia Chiappa, Matt Botvinick, Reena Jana, Dierdre Mulligan, and Deborah Raji for their valuable feedback on this paper  ... 
arXiv:2005.07572v3 fatcat:riswc6nvyzbypm5jt32xqzhypu

Granger causality vs. dynamic Bayesian network inference: a comparative study

Cunlu Zou, Jianfeng Feng
2009 BMC Bioinformatics  
One is the Granger causality approach, and the other is the dynamic Bayesian network inference approach. Both have at least a few thousand publications reported in the literature.  ...  A key issue is to choose which approach is used to tackle the data, in particular when they give rise to contradictory results.  ...  This toy model aims to test the causality sensitivity for the two approaches.  ... 
doi:10.1186/1471-2105-10-122 pmid:19393071 pmcid:PMC2691740 fatcat:gnjvydtd4bhhnmjh2uzlf2zhva

Granger causality vs. dynamic Bayesian network inference: a comparative study

Cunlu Zou, Katherine J Denby, Jianfeng Feng
2009 BMC Bioinformatics  
One is the Granger causality approach, and the other is the dynamic Bayesian network inference approach. Both have at least a few thousand publications reported in the literature.  ...  A key issue is to choose which approach is used to tackle the data, in particular when they give rise to contradictory results.  ...  This toy model aims to test the causality sensitivity for the two approaches.  ... 
doi:10.1186/1471-2105-10-401 fatcat:an2jk54mhbdilc3n3wjagnbupm

Explanatory Independence and Epistemic Interdependence: A Case Study of the Optimality Approach

A. Potochnik
2009 British Journal for the Philosophy of Science  
The value of optimality modeling has long been a source of contention amongst population biologists.  ...  Here I present a view of the optimality approach as at once playing a crucial explanatory role and yet also depending on external sources of confirmation.  ...  These models explicitly represent the genetic dynamics, which is why critics of the optimality approach consider this to be a superior approach to modeling evolution.  ... 
doi:10.1093/bjps/axp022 fatcat:4ormziuxanb3xninlgr3squr3u

Towards Actionable Business Intelligence: Can System Dynamics Help? [chapter]

Soroosh Nalchigar, Eric Yu, Steve Easterbrook
2014 Lecture Notes in Business Information Processing  
The proposed approach links and synthesizes two existing modeling frameworks, the Business Intelligence Model (BIM) and System Dynamics, in a systematic step-by-step way to assist decision makers in finding  ...  This paper proposes a model-based approach to support the analysis and selection of best alternative actions in adaptive enterprise contexts.  ...  The approach includes a set of suggestive heuristics to derive System Dynamics models from BIM models.  ... 
doi:10.1007/978-3-662-45501-2_18 fatcat:r36ajmn2yjfwpfetd4imihikwy

Approaches to Cognitive Modeling in Dynamic Systems Control

Daniel V. Holt, Magda Osman
2017 Frontiers in Psychology  
Much of human decision making occurs in dynamic situations where decision makers have to control a number of interrelated elements (dynamic systems control).  ...  models and models of causal learning.  ...  For example, Gonzalez et al. (2009) used this approach to model response times in a dynamic radar detection and decision making task.  ... 
doi:10.3389/fpsyg.2017.02032 pmid:29238315 pmcid:PMC5712578 fatcat:unek3h6iqvcqnijxk3lrocirqy

The effect of the system dynamics approach on understanding causal relationship skills in science education

Hasret Nuhoğlu
2010 Procedia - Social and Behavioral Sciences  
The aim of this research is to investigate the effect of system dynamics approach, in understanding of cause-effect relationship.  ...  In order to assess the sub problems of the study, a valid and reliable "Cause-Effect Relationship Scale" had been developed by the researcher.  ...  Students model concepts and cause-effect relationships among concepts with a dynamic concept map owing to system dynamics approach.  ... 
doi:10.1016/j.sbspro.2010.03.561 fatcat:3obwup4hjrbf3ec2ctqiwn4dbm

A model study for causal relationships between voltage and calcium dynamics

Pablo Chamorro, Daniele Marinazzo, Rafael Levi, Francisco B Rodriguez, Pablo Varona
2011 BMC Neuroscience  
For this study we applied Kernel Granger Causality (KGC), a recently proposed approach which allows a straightforward extension to the nonlinear case [6].  ...  We have addressed this question using conductance based models including a description of calcium dynamics.  ...  For this study we applied Kernel Granger Causality (KGC), a recently proposed approach which allows a straightforward extension to the nonlinear case [6] .  ... 
doi:10.1186/1471-2202-12-s1-p359 pmcid:PMC3240477 fatcat:yhp3lnb7szbntgri6c35sn6yuy

Invited Commentary: The Virtual Epidemiologist--Promise and Peril

A. V. Diez Roux
2014 American Journal of Epidemiology  
The process of building a systems model forces us to think about dynamic relationships and the ways in which they may play a role in the process we are studying.  ...  However, the validity of any causal conclusions derived from systems models hinges on the extent to which the models represent the fundamental dynamics relevant to the process in the real world.  ...  The process of building a systems model forces us to think about dynamic relationships and the ways in which they may play a role in the process we are studying.  ... 
doi:10.1093/aje/kwu270 pmid:25480822 fatcat:nmi3rxkw2neqnksxpmc7snezgm

Page 933 of The Journal of the Operational Research Society Vol. 56, Issue 8 [page]

2005 The Journal of the Operational Research Society  
System dynamics as a modelling method for BSC development In this article, we suggest the use of system dynamics (SD) as an approach to overcome the limitations to current BSC theory and usage mentioned  ...  Not only is the distinction between qualitative and quantitative modelling a common one in the SD literature, but a two-stage approach as suggested here to system dynamics modelling is also the ‘normal  ... 

A generalised fuzzy cognitive mapping approach for modelling complex systems

Abhishek Nair, Diana Reckien, M.F.A.M. van Maarseveen
2019 Applied Soft Computing  
This generalised FCM approach creates a new perspective and an alternative approach to model the behaviour of complex qualitative system dynamics using FCMs. addresses: a.nair@utwente.nl (A.  ...  FCMs in general are seen to have a number of advantages over traditional, quantitative modelling approaches.  ...  Acknowledgements We would like to thank Dr. Shuaib Lwasa and Dr.  ... 
doi:10.1016/j.asoc.2019.105754 fatcat:7scae6bhnfcvtabj2453bugfsi

Variance-Based Spillover Analysis between Stock Markets: A Time Varying Parameter Approach

A. Özün, H. M. Ertuğrul
2014 Acta Physica Polonica. A  
As an embedded analysis, we follow a dynamic approach by using the Kalman ltering as a time varying parameter model to depict the time varying interaction between stock markets volatilities.  ...  This paper proposes a variance-based spillover impact analysis embedded with a dynamic Kalman ltering in order to detect a causality relationship from the US stock markets into the European and emerging  ...  We base our dynamic approach on a classical reference of Harvey [10] that introduces the Kalman lter approach. The Kalman lter approach is based on a form of state space representation.  ... 
doi:10.12693/aphyspola.125.155 fatcat:6iihtptsnbdkbcioq4i2h62qp4

Structure Mapping for Transferability of Causal Models [article]

Purva Pruthi, Javier González, Xiaoyu Lu, Madalina Fiterau
2020 arXiv   pre-print
A learned causal dynamics model can be used to transfer between variants of an environment with exchangeable perceptual features among objects but with the same underlying causal dynamics.  ...  We demonstrate the advantages of our approach in a gridworld setting by combining causal model-based approach with model-free approach in reinforcement learning.  ...  techniques. • We formulate and evaluate the causal dynamics model combined with model-free approach on a toy gridworld problem as a proof-of-concept. • We formulate transfer learning as a structure mapping  ... 
arXiv:2007.09445v1 fatcat:ui6objfmffhwrcrzjef2e2rfl4
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