Pitman closeness of predictors of future order statistics for two parameter exponential distribution
S. MirMostafaee (),
Jafar Ahmadi () and
Narjes Sadeghian
Computational Statistics, 2015, vol. 30, issue 4, 1163-1183
Abstract:
In this paper, the Pitman closeness of predictors for a future order statistic coming from a two parameter exponential distribution is discussed. The optimum equivariant predictor using the Pitman closeness criterion is derived and compared with the best invariant predictor and the best unbiased predictor. The predictors are obtained on the basis of observed record values. Exact expressions for the required Pitman closeness probabilities are derived when both parameters are considered to be unknown. Similar results are obtained for the predictors of the mean of a future sample from exponential distribution. Several tables which contain numerical computations, are provided in order to compare the predictors in the sense of Pitman’s measure of closeness. Copyright Springer-Verlag Berlin Heidelberg 2015
Keywords: Best invariant predictor; Best unbiased predictor; Pitman closest equivariant predictor; Pitman’s measure of closeness; Record values (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1007/s00180-015-0554-1 (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:spr:compst:v:30:y:2015:i:4:p:1163-1183
Ordering information: This journal article can be ordered from
http://www.springer.com/statistics/journal/180/PS2
DOI: 10.1007/s00180-015-0554-1
Access Statistics for this article
Computational Statistics is currently edited by Wataru Sakamoto, Ricardo Cao and Jürgen Symanzik
More articles in Computational Statistics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().