Linguistic Descriptions As a Modeling Tool For Multivariate Time Series

DOI

10.2991/ifsa-eusflat-15.2015.138How to use a DOI?

Keywords

Multivariate time series, evaluative linguistic expressions, association analysis, Perception based Logic Deduction

Abstract

We propose linguistic associations mining as a technique to create the models of the multivariate time series. We define various linguistic evaluative expressions on the range of the values of the time series and variables derived from them. We mine linguistic associations then and interpret them as IF-THEN rules in the framework of Perception based Logic Deduction (PbLD). The mined rules provide the linguistic descriptions of various relationships between the time series. We showcase our suggested methodology in a macroeconomic example where we compare our approach with Dynamic Stochastic General Equilibrium (DSGE) model, that is frequently used in the macroeconomic modeling.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Pavel Rusnok
PY  - 2015/06
DA  - 2015/06
TI  - Linguistic Descriptions As a Modeling Tool For Multivariate Time Series
BT  - Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology
PB  - Atlantis Press
SP  - 981
EP  - 986
SN  - 1951-6851
UR  - https://doi.org/10.2991/ifsa-eusflat-15.2015.138
DO  - 10.2991/ifsa-eusflat-15.2015.138
ID  - Rusnok2015/06
ER  -