ML-estimation in the location-scale-shape model of the generalized logistic
Klaus Abberger · KOPS (University of Konstanz) · 2002
A three parameter (location, scale, shape) generalization of the lo- gistic distribution is fitted to data. Local maximum likelihood estimators of the parameters are derived. Although the likelihood function is unbounded, the like- lihood equations have a consistent root. ML-estimation combined with the ECM algorithm allows the distribution to be easily fitted to data.