RT Journal Article
T1 Some new statistics for testing hypotheses in parametric models
A1 Morales González, Domingo
A1 Pardo Llorente, Leandro
A1 Vadja, Igor
AB The paper deals with simple and composite hypotheses in statistical models with i.i.d. observations and with arbitrary families dominated by a finite measures and parametrized by vector-valued variables. It introduces phi-divergence testing statistics as alternatives to the classical ones: the generalized likelihood ratio and the statistics of Wald and Rao. It is shown that, under the assumptions of standard type about hypotheses and model densities, the results about asymptotic distribution of the classical statistics established so far for the counting and Lebesgue dominating measures (discrete and continuous models) remain true also in the general case. Further, these results are extended to the phi-divergence statistics with smooth convex functions phi. The choice of phi-divergence statistics optimal from the point of view of power is discussed and illustrated by several examples.
PB Academic Press
SN 0047-259X
YR 1997
FD 1997-07
LK https://hdl.handle.net/20.500.14352/57879
UL https://hdl.handle.net/20.500.14352/57879
LA eng
NO UCM
NO DGICYT
NO GA
DS Docta Complutense
RD 9 abr 2025