Stochastic cusp catastrophe model and its Bayesian computations.

This paper revitalizes the investigation of the classical cusp catastrophe model in catastrophe theory and tackles the unsolved statistical inference problem concerning stochastic cusp differential equation. This model is challenging because its associated transition density hence the likelihood function is analytically intractable. We propose a novel Bayesian approach combining Hamiltonian Monte Carlo with two likelihood approximation methods, namely, Euler approximation and Hermite expansion.

A stochastic biomechanical model for risk and risk factors of non-contact anterior cruciate ligament injuries.

Gender has been identified as a risk factor for non-contact anterior cruciate ligament (ACL) injuries. Although some possible biomechanical risk factors underlying the gender differences in the risk for non-contact ACL injuries have been identified, they have not been quantitatively confirmed yet because of the descriptive nature of the traditional epidemiological methods. The purpose of this study was to validate a stochastic biomechanical model for the risk and risk factors for non-contact ACL injuries.