RT Journal Article
T1 A comparison of some estimators of the mixture proportion of mixed normal distributions
A1 Pardo Llorente, María del Carmen
AB Fisher's method of maximum likelihood breaks down when applied to the problem of estimating the five parameters of a mixture of two normal densities from a continuous random sample of size n. Alternative methods based on minimum-distance estimation by grouping the underlying variable are proposed. Simulation results compare the efficiency as well as the robustness under symmetric departures from component normality of these estimators. Our results indicate that the estimator based on Rao's divergence is better than other classic ones.
PB Elsevier Science Bv
SN 0377-0427
YR 1997
FD 1997-10-28
LK https://hdl.handle.net/20.500.14352/57835
UL https://hdl.handle.net/20.500.14352/57835
LA eng
NO This work was supported by Grant DGICYT PB94-0308
NO DGICYT
DS Docta Complutense
RD 6 abr 2025