Felipe Ortega, ÁngelPardo Llorente, Leandro2023-06-202023-06-202007-050094-965510.1080/10629360600890154https://hdl.handle.net/20.500.14352/49892loglinear model, quasi-independence, maximum likelihood, minimum powerdivergence estimatorWe study the minimum power-divergence estimator, introduced and studied by N. Cressie and T. R. C. Read [Multinomial goodness-of-fit tests. J. R. Stat. Soc., Ser. B 46, 440–464 (1984), in the loglinear model of quasi-independence. A simulation study illustrates that minimum chi-squared estimator and Cressie-Read estimator are good alternatives to the classical maximum-likelihood estimator for this problem. The estimator obtained for = 2 is the most robust and efficient estimator among the family of the minimum power estimators.engjournal articlehttp://www.tandfonline.com/doi/pdf/10.1080/10629360600890154http://www.tandfonline.comrestricted access517.9Loglinear ModelQuasi-IndependenceMaximum LikelihoodMinimum Power-Divergence EstimatorMinimumDistanceComputer ScienceInterdisciplinary ApplicationsStatistics & ProbabilityEcuaciones diferenciales1202.07 Ecuaciones en Diferencias