Incompletely known sample spaces: Models and human intuitions
Date
2019
Authors
Smithson, Michael
Journal Title
Journal ISSN
Volume Title
Publisher
Proceedings of Machine Learning Research
Abstract
This paper surveys models and human intuitions about incompletely known "sample spaces" (Ω). Given that there are very few guidelines for how best to form such beliefs when Ω is incompletely known, and there is very little research on the psychology behind beliefs about Ω, this survey is preliminary and brings in ideas and models from probability and statistics, biology, and psychology. Pilot experimental studies of how people estimate the cardinality of Ω when given sample information from it are presented, demonstrating that to a surprising extent their estimates correspond with those produced by normative statistical models. The paper concludes by outlining future directions for a research program on this topic.
Description
Keywords
sample space, cardinality, capturerecapture sample, Dirichlet process, imprecise Dirichlet model, human intuition
Citation
Collections
Source
Proceedings of the Eleventh International Symposium on Imprecise Probabilities: Theories and Applications ISIPTA 2019
Type
Conference paper
Book Title
Entity type
Access Statement
Free Access via publisher website
License Rights
DOI
Restricted until
2099-12-31