Weather Simulation Uncertainty Estimation Using Bayesian Hierarchical Models

Bayesian Estimation in Hierarchical Models

Bayesian data analysis involves describing data by meaningful mathematical models, and allocating credibility to parameter values that are consistent with the data and with prior knowledge. The Bayesian approach is ideally suited for constructing hierarchical models, which are useful for data structures with multiple levels, such as data from individuals who are members of groups which in turn ...

Bayesian Hierarchical Models 1 Running head: BAYESIAN HIERARCHICAL MODELS Bayesian Hierarchical Models

Planning under Uncertainty using Nonparametric Bayesian Models

The ability to plan actions autonomously to achieve predefined objectives in the presence of environmental uncertainties is critical to the success of many Unmanned Aerial Vehicle missions. One way to plan in the presence of such uncertainties is by learning a model of the environment through Bayesian inference, and using this model to improve the predictive capability of the planning algorithm...

Calibrating Subjective Probabilities Using Hierarchical Bayesian Models

Abstract. A body of psychological research has examined the correspondence between a judge’s subjective probability of an event’s outcome and the event’s actual outcome. The research generally shows that subjective probabilities are noisy and do not match the “true” probabilities. However, subjective probabilities are still useful for forecasting purposes if they bear some relationship to true ...

Identifying outliers in Bayesian hierarchical models: a simulation-based approach

A variety of simulation-based techniques have been proposed for detection of divergent behaviour at each level of a hierarchical model. We investigate a diagnostic test based on measuring the conflict between two independent sources of evidence regarding a parameter: that arising from its predictive prior given the remainder of the data, and that arising from its likelihood. This test gives ris...