An improved methodology for quantifying causality in complex ecological systems.

ABSTRACT: This paper provides a statistical methodology for quantifying causality in complex dynamical systems, based on analysis of multidimensional time series data of the state variables. The methodology integrates Granger's causality analysis based on the log-likelihood function expansion (Partial pair-wise causality), and Akaike's power contribution approach over the whole frequency domain (Total causality). The proposed methodology addresses a major drawback of existing methodologies namely, their inability to use time series observation of state variables to quantify causality in complex systems. We first perform a simulation study to verify the efficacy of the methodology using data generated by several multivariate autoregressive processes, and its sensitivity to data sample size. We demons

SUBMITTER: Solvang HK 

PROVIDER: S-EPMC6347266 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature