A two-stage Bayesian downscaling model estimates county-level opioid use disorder risk from state-level survey counts, but its validation uses data generated by the model itself and shows large county-level errors.
On the behavior of the Generalized Alignment Index (GALI) method for regular motion in multidimensional Hamiltonian systems
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
We investigate the behavior of the Generalized Alignment Index of order $k$ (GALI$_k$) for regular orbits of multidimensional Hamiltonian systems. The GALI$_k$ is an efficient chaos indicator, which asymptotically attains positive values for regular motion when $2\leq k \leq N$, with $N$ being the dimension of the torus on which the motion occurs. By considering several regular orbits in the neighborhood of two typical simple, stable periodic orbits of the Fermi-Pasta-Ulam-Tsingou (FPUT) $\beta$ model for various values of the system's degrees of freedom, we show that the asymptotic GALI$_k$ values decrease when the index's order $k$ increases and when the orbit's energy approaches the periodic orbit's destabilization energy where the stability island vanishes, while they increase when the considered regular orbit moves further away from the periodic one for a fixed energy. In addition, performing extensive numerical simulations we show that the index's behavior does not depend on the choice of the initial deviation vectors needed for its evaluation.
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A Bayesian Spatio-Temporal Top-Down Framework for Estimating Opioid Use Disorder Risk Under Data Sparsity
A two-stage Bayesian downscaling model estimates county-level opioid use disorder risk from state-level survey counts, but its validation uses data generated by the model itself and shows large county-level errors.