Multi-event decision making over multivariate time series

Chun-Kit Ngan, Alexander Brodsky and Jessica Lin

International Journal of Information and Decision Sciences, 2013, vol. 5, issue 3, 263-282

Abstract: We propose a multidimentional time-point model and algorithm to solve multi-event expert query parametric estimation (ME-EQPE) problems over multivariate time series. Our proposed model and algorithm combine the strengths of both domain-knowledge-based and formal-learning-based approaches to learn optimal decision parameters for maximising utility over multivariate time series. More specifically, our approach solves the decision optimisation problems to maximise the utility from multiple decision time points, as well as maintaining an optimality of the learned multiple sets of decision parameters in their respective events during the computations. We show that our approach produces a reasonable forecasting result by using the learned multiple sets of decision parameters.

Keywords: statistical learning; prediction; multivariate time series; decision support; multi-event decision making; modelling; expert query parametric estimation; decision optimisation; forecasting. (search for similar items in EconPapers)
Date: 2013
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=55925 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijidsc:v:5:y:2013:i:3:p:263-282

Access Statistics for this article

More articles in International Journal of Information and Decision Sciences from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().