Mean, mode or median? The score mean

Zdeněk Fabián

Communications in Statistics - Theory and Methods, 2021, vol. 50, issue 10, 2360-2370

Abstract: A continuous random variable can be uniquely represented by the score function of distribution, i.e. a scalar-valued function describing the influence of a data item on the typical value of the distribution. There are at most two relevant scalar-valued scores based on two basic transformations: the “natural” one, useful for estimating parameters of parametric distributions by the generalized moment method; and the “universal” one, which is a basis for the score function of distribution. The score mean, the zero of the score function of distribution, represents the typical value of the distribution in the sense of the value which is most likely to be sampled. Both scores are often identical to each other. The derivative of the score function of distribution is the weight function of this distribution. The main result is that sums of score random variables obey the central limit theorem and can be used for directly estimating the score mean without use of any current estimator.

Date: 2021
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2019.1666142 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:lstaxx:v:50:y:2021:i:10:p:2360-2370

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20

DOI: 10.1080/03610926.2019.1666142

Access Statistics for this article

Communications in Statistics - Theory and Methods is currently edited by Debbie Iscoe

More articles in Communications in Statistics - Theory and Methods from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().