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Identifying dynamic spillovers of crime with a causal approach to model selection
2018
Quantitative Economics
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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
2016
Philosophy of Science
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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]
2020
arXiv
pre-print
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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
2009
BMC Bioinformatics
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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
2009
BMC Bioinformatics
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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
2009
British Journal for the Philosophy of Science
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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]
2014
Lecture Notes in Business Information Processing
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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
2017
Frontiers in Psychology
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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
2010
Procedia - Social and Behavioral Sciences
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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
2011
BMC Neuroscience
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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
2014
American Journal of Epidemiology
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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
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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
2019
Applied Soft Computing
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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
2014
Acta Physica Polonica. A
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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]
2020
arXiv
pre-print
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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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