Reduction functions for the variance function of one-parameter natural exponential family
Xiongzhi Chen
Statistics & Probability Letters, 2018, vol. 137, issue C, 319-325
Abstract:
We show that, when a random variable has a parametric distribution as a member of an infinitely divisible natural exponential family whose induced measure is absolutely continuous with respect to its basis measure, there exists a deterministic function, referred to as “reduction function”, such that the random variable transformed by this function is an unbiased estimator of the variance of the random variable. Our result can be used in estimating latent structure in high-dimensional data and in implementing iterative reweighted least squares for generalized linear models.
Keywords: Infinitely divisibility; Natural exponential family; Reduction function; Variance function (search for similar items in EconPapers)
Date: 2018
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167715218300555
Full text for ScienceDirect subscribers only
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:eee:stapro:v:137:y:2018:i:c:p:319-325
Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01
DOI: 10.1016/j.spl.2018.02.010
Access Statistics for this article
Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul
More articles in Statistics & Probability Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().