Arbeitspapier
Polynomial chaos expansion: Efficient evaluation and estimation of computational models
Polynomial chaos expansion (PCE) provides a method that enables the user to represent a quantity of interest (QoI) of a model's solution as a series expansion of uncertain model inputs, usually its parameters. Among the QoIs are the policy function, the second moments of observables, or the posterior kernel. Hence, PCE sidesteps the repeated and time consuming evaluations of the model's outcomes. The paper discusses the suitability of PCE for computational economics. We, therefore, introduce to the theory behind PCE, analyze the convergence behavior for different elements of the solution of the standard real business cycle model as illustrative example, and check the accuracy, if standard empirical methods are applied. The results are promising, both in terms of accuracy and efficiency.
- Language
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Englisch
- Bibliographic citation
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Series: Volkswirtschaftliche Diskussionsreihe ; No. 341
- Classification
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Wirtschaft
Bayesian Analysis: General
Estimation: General
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Computational Techniques; Simulation Modeling
- Subject
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Polynomial Chaos Expansion
parameter inference
parameter uncertainty
solution methods
- Event
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Geistige Schöpfung
- (who)
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Fehrle, Daniel
Heiberger, Christopher
Huber, Johannes
- Event
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Veröffentlichung
- (who)
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Universität Augsburg, Institut für Volkswirtschaftslehre
- (where)
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Augsburg
- (when)
-
2020
- Handle
- Last update
-
10.03.2025, 11:42 AM CET
Data provider
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ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Fehrle, Daniel
- Heiberger, Christopher
- Huber, Johannes
- Universität Augsburg, Institut für Volkswirtschaftslehre
Time of origin
- 2020
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Uncertainty quantification for a blood pump device with generalized polynomial chaos expansion
Uncertainty Quantification for a Blood Pump Device with Generalized Polynomial Chaos Expansion
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Comparison of the performance and reliability between improved sampling strategies for polynomial chaos expansion
Efficient, perfect polynomial random number generators
Applications of arbitrary polynomial chaos in electrical systems
Schnell konvergierender Polynomial Expansion Multiuser Detektor mit niedriger Komplexität
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Polynomial chaos expansion: efficient evaluation and estimation of computational models
Polynomial chaos expansion: Efficient evaluation and estimation of computational models
Polynomial chaos expansion: efficient evaluation and estimation of computational models
Polynomial Chaos Expansion mit räumlich adaptiven Sparse Grids
Uncertainty quantification for a blood pump device with generalized polynomial chaos expansion
Uncertainty Quantification for a Blood Pump Device with Generalized Polynomial Chaos Expansion
Uncertainty Quantification via Polynomial Chaos Expansion – Methods and Applications for Optimization of Power Systems
Comparison of the performance and reliability between improved sampling strategies for polynomial chaos expansion
Efficient, perfect polynomial random number generators
Applications of arbitrary polynomial chaos in electrical systems
Schnell konvergierender Polynomial Expansion Multiuser Detektor mit niedriger Komplexität