A class of statistical models to weaken independence in two-way contingency tables
| dc.creator | Carlini, Enrico | |
| dc.creator | Rapallo, Fabio | |
| dc.date | 2008-03-11 | |
| dc.date | 2008-04-29 | |
| dc.date.accessioned | 2026-07-07T09:35:27Z | |
| dc.date.available | 2026-07-07T09:35:27Z | |
| dc.description | In this paper we study a new class of statistical models for contingency tables. We define this class of models through a subset of the binomial equations of the classical independence model. We use some notions from Algebraic Statistics to compute their sufficient statistic, and to prove that they are log-linear. Moreover, we show how to compute maximum likelihood estimates and to perform exact inference through the Diaconis-Sturmfels algorithm. Examples show that these models can be useful in a wide range of applications. | |
| dc.description | A theorem has been removed because of a gap in the proof. Minor style changes | |
| dc.identifier | https://arxiv.org/abs/0803.1582 | |
| dc.identifier | http://arxiv.org/abs/0803.1582 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/159835 | |
| dc.subject | Statistics Theory | |
| dc.subject | Algebraic Geometry | |
| dc.subject | Methodology | |
| dc.subject | 62H17 (Primary); 60A99, 65C60, 13P10 (Secondary) | |
| dc.title | A class of statistical models to weaken independence in two-way contingency tables | |
| dc.type | text |