Selecting Balls From Urns With Partial Replacement Rules
| dc.contributor.author | Julian Burden | |
| dc.contributor.author | Chandramauli Chakraborty | |
| dc.contributor.author | Q. Z. Fang | |
| dc.contributor.author | Lai-Jiu Lin | |
| dc.contributor.author | Nasser Malibari | |
| dc.contributor.author | Sammi Matoush | |
| dc.contributor.author | Isaiah Milbank | |
| dc.contributor.author | Zahan Parekh | |
| dc.contributor.author | Martín Prado | |
| dc.contributor.author | Rachael Ren | |
| dc.coverage.spatial | Bolivia | |
| dc.date.accessioned | 2026-03-22T19:25:44Z | |
| dc.date.available | 2026-03-22T19:25:44Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | Consider an urn with an initial state of R red balls and W white balls. Draw a ball from the urn, uniformly at random, and note its color. If the ball is white, do not replace it; if the ball is red, do replace it. Define this sampling rule to be "Preferential". We study the random variable X denoting the number of white balls drawn under the Preferential sampling rule for a sample size n. It is known that the expected number of X is bounded below by 3nW/(4N), and bounded above by nW/N. In this paper we improve the lower bound, give a heuristic for the best possible lower bound, and we explore some properties of a generalization of this sampling rule, we call "Super-Preferential", where the probability of retaining a white ball is w and the probability of retaining a red ball is r. | |
| dc.identifier.doi | 10.46787/pump.v7i0.4251 | |
| dc.identifier.uri | https://doi.org/10.46787/pump.v7i0.4251 | |
| dc.identifier.uri | https://andeanlibrary.org/handle/123456789/75997 | |
| dc.language.iso | en | |
| dc.relation.ispartof | The PUMP Journal of Undergraduate Research | |
| dc.source | Gettysburg College | |
| dc.subject | Computer science | |
| dc.subject | Combinatorics | |
| dc.subject | Mathematics | |
| dc.title | Selecting Balls From Urns With Partial Replacement Rules | |
| dc.type | article |