Regularized e-processes: anytime valid inference with knowledge-based
efficiency gains
Regularized e-processes: anytime valid inference with knowledge-based
efficiency gains
Classical statistical methods have theoretical justification when the sample size is predetermined by the data-collection plan. In applications, however, it's often the case that sample sizes aren't predetermined; instead, investigators might use the data observed along the way to make on-the-fly decisions about when to stop data collection. Since those …