Neyer d-optimal test
The Neyer d-optimal test is a sensitivity test. It can be used to answer questions such as "How far can a carton of eggs fall, on average, before one breaks?" If these egg cartons are very expensive,
Prophet inequality
In the theory of online algorithms and optimal stopping, a prophet inequality is a bound on the expected value of a decision-making process that handles a sequence of random inputs from known probabil
Haybittle–Peto boundary
The Haybittle–Peto boundary is a rule for deciding when to stop a clinical trial prematurely. It is named for John Haybittle and Richard Peto. The typical clinical trial compares two groups of patient
Bayesian optimization
Bayesian optimization is a sequential design strategy for global optimization of black-box functions that does not assume any functional forms. It is usually employed to optimize expensive-to-evaluate
Response surface methodology
In statistics, response surface methodology (RSM) explores the relationships between several explanatory variables and one or more response variables. The method was introduced by George E. P. Box and
Multi-armed bandit
In probability theory and machine learning, the multi-armed bandit problem (sometimes called the K- or N-armed bandit problem) is a problem in which a fixed limited set of resources must be allocated
Pocock boundary
The Pocock boundary is a method for determining whether to stop a clinical trial prematurely. The typical clinical trial compares two groups of patients. One group are given a placebo or conventional
Thompson sampling
Thompson sampling, named after William R. Thompson, is a heuristic for choosing actions that addresses the in the multi-armed bandit problem. It consists of choosing the action that maximizes the expe