Several of our current PhD candidates and fellow researchers at the Data Science Institute have published, or in the proccess of publishing, papers to present their research.
@inproceedings{Nadler:2019:10.1109/SITIS.2019.00106,
author = {Nadler, P and Arcucci, R and Guo, YK},
doi = {10.1109/SITIS.2019.00106},
pages = {649--656},
title = {Data assimilation for parameter estimation in economic modelling},
url = {http://dx.doi.org/10.1109/SITIS.2019.00106},
year = {2019}
}
TY - CPAPER
AB - We propose a data assimilation approach for latent parameter estimation in economic models. We describe a dynamic model of an economic system with latent state variables describing the relationship of economic entities over time as well as a stochastic volatility component. We show and discuss the model's relationship with data assimilation and how it is derived. We apply it to conduct a multivariate analysis of the cryptocurrency ecosystem. Combining these approaches opens a new dimension of analysis to economic modelling. Economics, Multivariate Analysis, Dynamical System, Bitcoin, Data Assimilation.
AU - Nadler,P
AU - Arcucci,R
AU - Guo,YK
DO - 10.1109/SITIS.2019.00106
EP - 656
PY - 2019///
SP - 649
TI - Data assimilation for parameter estimation in economic modelling
UR - http://dx.doi.org/10.1109/SITIS.2019.00106
ER -