New Developments for Bayesian statistical models and computational methods.

贝叶斯方法的统计分析提供了一个灵活的理论处理推理的存在不确定性。因此，贝叶斯方法能够在复杂系统领域进行科学发现，其中建模和计算方法的新发展至关重要。进一步成功的重大障碍包括在制定和验证模型、处理大数据集以及开发有效的计算方法方面的挑战。该项目的主要目的是开发新的贝叶斯建模和计算方法，以解决这些挑战，并具有广泛的应用。

Bayesian methods of statistical analysis provide a flexible theory for addressing inference in the presence of uncertainty. Consequently Bayesian methods have enabled scientific discovery in areas characterised as complex systems where new developments in modelling and computational methods have been crucial. Significant barriers to further success involve challenges in formulating and validating models, dealing with large data sets, and developing efficient computational methods. The principal aim of this project is to develop new Bayesian modelling and computational methodology which address these challenges with broad application.