Asymptotic normality of generalized maximum spacing estimators for multivariate observations

Sammanfattning

In this paper, the maximum spacing method is considered for multivariate observations. Nearest neighbor balls are used as a multidimensional analogue to univariate spacings. A class of information-type measures is used to generalize the concept of maximum spacing estimators of model parameters. Asymptotic normality of these generalized maximum spacing estimators is proved when the assigned model class is correct, that is, the true density is a member of the model class.

Nyckelord

asymptotic normality; consistency; divergence measures; maximum spacing estimation; nearest neighbor balls

Publicerad i

Scandinavian Journal of Statistics
2020, volym: 47, nummer: 3, sidor: 968-989

SLU författare

• Kuljus, Kristi

  • Institutionen för skogsekonomi, Sveriges lantbruksuniversitet
    

• Ranneby, Bo

  • Institutionen för skogsekonomi, Sveriges lantbruksuniversitet
    

UKÄ forskningsämne

Sannolikhetsteori och statistik

Publikationens identifierare

• DOI: https://doi.org/10.1111/sjos.12436

Permanent länk till denna sida (URI)

https://res.slu.se/id/publ/103114