| Full text | |
| Author(s): |
Total Authors: 3
|
| Affiliation: | [1] Univ Sao Paulo, Dept Stat, Sao Paulo - Brazil
[2] Univ Fed Sao Carlos, Dept Stat, Sao Carlos, SP - Brazil
Total Affiliations: 2
|
| Document type: | Journal article |
| Source: | AMERICAN STATISTICIAN; v. 71, n. 4, p. 336-343, 2017. |
| Web of Science Citations: | 1 |
| Abstract | |
Teaching how to derive minimax decision rules can be challenging because of the lack of examples that are simple enough to be used in the classroom. Motivated by this challenge, we provide a new example that illustrates the use of standard techniques in the derivation of optimal decision rules under the Bayes and minimax approaches. We discuss how to predict the value of an unknown quantity,theta.epsilon [0, 1], given the opinions of n experts. An important example of such crowdsourcing problem occurs in modern cosmology, where theta indicates whether a given galaxy is merging or not, and Y-1,..., Y-n are the opinions from n astronomers regarding theta We use the obtained prediction rules to discuss advantages and disadvantages of the Bayes andminimax approaches to decision theory. The material presented here is intended to be taught to first- year graduate students. (AU) | |
| FAPESP's process: | 17/03363-8 - Interpretability and efficiency in hypothesis tests |
| Grantee: | Rafael Izbicki |
| Support Opportunities: | Regular Research Grants |
| FAPESP's process: | 14/25302-2 - A flexible approach to high-dimensional conditional density estimation |
| Grantee: | Rafael Izbicki |
| Support Opportunities: | Regular Research Grants |