Eigenvalue Analysis via Kernel Density Estimation
arXiv:1810.06276
Originality Synthesis-oriented
AI Analysis
For researchers analyzing system dynamics models, this offers a potentially efficient multivariate sensitivity analysis, but the abstract lacks empirical validation.
The paper proposes a new eigenvalue sensitivity analysis method for system dynamics models using Mutual Information estimated via Kernel Density Estimation. No concrete results are provided.
In this paper, we propose an eigenvalue analysis -- of system dynamics models -- based on the Mutual Information measure, which in turn will be estimated via the Kernel Density Estimation method. We postulate that the proposed approach represents a novel and efficient multivariate eigenvalue sensitivity analysis.