Pérez, T.Pardo Llorente, Julio Ángel2023-06-202023-06-202004-040893-965910.1016/s0893-9659(04)00040-0https://hdl.handle.net/20.500.14352/50248In the present work, the problem of estimating parameters of statistical models for categorical data is analyzed. The minimum K-phi-divergence estimator is obtained minimizing the K-phi-divergence measure between the theoretical and the empirical probability vectors. Its asymptotic properties are obtained. Rom a simulation study, the conclusion is that our estimator emerges as an attractive alternative to the classical maximum likelihood estimator.engjournal articlehttp://www.sciencedirect.com/science/article/pii/S0893965904900766http://www.sciencedirect.comrestricted access519.22Categorical dataK¢-divergenceMinimum K¢-divergence estimatorConsistencySimulation.Estadística matemática (Matemáticas)1209 Estadística