Martín Apaolaza, NíriamPardo Llorente, Leandro2023-06-202023-06-202008-090047-259X10.1016/j.jmva.2008.01.002https://hdl.handle.net/20.500.14352/50253In this paper we consider categorical data that are distributed according to a multinomial, product-multinomial or Poisson distribution whose expected values follow a log-linear model and we study the inference problem of hypothesis testing in a log-linear model setting. The family of test statistics considered is based on the family of phi-divergence measures. The unknown parameters in the log-linear model under consideration are also estimated using phi-divergence measures: Minimum phi-divergence estimators. A simulation study is included to find test statistics that offer an attractive alternative to the Pearson chi-square and likelihood-ratio test statistics.engjournal articlehttp://www.sciencedirect.com/science/article/pii/S0047259X08000171http://www.sciencedirect.com/restricted access517.15asymptotic distributionsnested hypothesesPoisson samplingmultinomial samplingproduct-multinomial samplingminimum phi-divergence estimatorphi-divergence test statisticsLoglinear models.Estadística matemática (Matemáticas)1209 Estadística