Bayesian experimental design is a statistical approach that integrates Bayesian principles with the design of experiments. It focuses on the process of planning and conducting experiments in such a way that the data collected can provide the most informative insights regarding the parameters of interest. Here are some key elements of Bayesian experimental design: 1. **Prior Knowledge**: Bayesian methods allow the incorporation of prior information or beliefs about the parameters being studied. This prior knowledge can come from previous experiments, expert opinions, or literature.
Articles by others on the same topic
There are currently no matching articles.