Kuljus, Kristi
- Department of Forest Economics, Swedish University of Agricultural Sciences
Research article2020Peer reviewedOpen access
Asymptotic normality of generalized maximum spacing estimators for multivariate observations
Kuljus, Kristi; Ranneby, Bo
Abstract
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.
Keywords
asymptotic normality; consistency; divergence measures; maximum spacing estimation; nearest neighbor balls
Published in
Scandinavian Journal of Statistics
2020, volume: 47, number: 3, pages: 968-989
SLU Authors
Ranneby, Bo
- Department of Forest Economics, Swedish University of Agricultural Sciences
- Department of Forest Economics, Swedish University of Agricultural Sciences
UKÄ Subject classification
Probability Theory and Statistics
Publication identifier
- DOI: https://doi.org/10.1111/sjos.12436
Permanent link to this page (URI)
https://res.slu.se/id/publ/103114