Show simple item record

dc.contributor.authorPotgieter, C.J.
dc.contributor.authorLombard, F.
dc.date.accessioned2014-01-13T13:37:00Z
dc.date.available2014-01-13T13:37:00Z
dc.date.issued2012
dc.identifier.citationPotgieter, C.J. & Lombard, F. 2012. Nonparametric estimation of location and scale parameters. Computational statistics and data analysis, 56(12):4327-4337. [https://doi.org/10.1016/j.csda.2012.03.021]en_US
dc.identifier.issn0167-9473
dc.identifier.urihttp://hdl.handle.net/10394/9916
dc.identifier.urihttps://doi.org/10.1016/j.csda.2012.03.021
dc.identifier.urihttp://www.sciencedirect.com/science/article/pii/S0167947312001478?via%3Dihub
dc.description.abstractTwo random variables X and Y belong to the same location-scale family if there are constants μ and σ such that Y and μ+σX have the same distribution. In this paper we consider non-parametric estimation of the parameters μ and σ under minimal assumptions regarding the form of the distribution functions of X and Y. We discuss an approach to the estimation problem that is based on asymptotic likelihood considerations. Our results enable us to provide a methodology that can be implemented easily and which yields estimators that are often near optimal when compared to fully parametric methods. We evaluate the performance of the estimators in a series of Monte Carlo simulations.en_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.subjectLocation-scale familiesen_US
dc.subjectasymptotic likelihooden_US
dc.subjectnonparametric estimationen_US
dc.titleNonparametric estimation of location and scale parametersen_US
dc.typeArticleen_US
dc.contributor.researchID12950149 - Lombard, Frederick


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record