### Impacto

### Downloads

Downloads per month over past year

Pardo Llorente, Leandro and Martín Apaolaza, Níriam
(2011)
*On the comparison of the pre-test and shrinkage phi-divergence test estimators for the symmetry model of categorical data.*
Journal of Computational and Applied Mathematics, 235
(5).
pp. 1160-1179.
ISSN 0377-0427

PDF
Restringido a Repository staff only 340kB |

Official URL: http://www.sciencedirect.com/science/article/pii/S0377042710004243

URL | URL Type |
---|---|

http://www.sciencedirect.com/ | Publisher |

## Abstract

The estimation problem of the parameters in a symmetry model for categorical data has been considered for many authors in the statistical literature (for example, Bowker (1948) [1], Ireland et al. (1969) [2], Quade and Salama (1975) [3] Cressie and Read (1988) [4], Menendez et al. (2005) [5]) without using uncertain prior information. It is well known that many new and interesting estimators, using uncertain prior information, have been studied by a host of researchers in different statistical models, and many papers have been published on this topic (see Saleh (2006) [9] and references therein). In this paper, we consider the symmetry model of categorical data and we study, for the first time, some new estimators when non-sample information about the symmetry of the probabilities is considered. The decision to use a "restricted" estimator or an "unrestricted" estimator is based on the outcome of a preliminary test, and then a shrinkage technique is used. It is interesting to note that we present a unified study in the sense that we consider not only the maximum likelihood estimator and likelihood ratio test or chi-square test statistic but we consider minimum phi-divergence estimators and phi-divergence test statistics. Families of minimum phi-divergence estimators and phi-divergence test statistics are wide classes of estimators and test statistics that contain as a particular case the maximum likelihood estimator, likelihood ratio test and chi-square test statistic. In an asymptotic set-up, the biases and the risk under the squared loss function for the proposed estimators are derived and compared. A numerical example clarifies the content of the paper.

Item Type: | Article |
---|---|

Uncontrolled Keywords: | Minimum phi-divergence estimator; Phi-divergence statistics; Preliminary test estimator; Symmetry model; Marginal homogeneity; Contingency-tables |

Subjects: | Sciences > Mathematics > Mathematical statistics |

ID Code: | 17332 |

Deposited On: | 05 Dec 2012 09:18 |

Last Modified: | 16 Nov 2018 19:25 |

### Origin of downloads

Repository Staff Only: item control page