Equivariance and Generalized Inference in Two-Sample Location-Scale Families
Joint Authors
Nkurunziza, Sévérien
Chen, Fuqi
Source
Journal of Probability and Statistics
Issue
Vol. 2011, Issue 2011 (31 Dec. 2011), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2011-10-18
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
We are interested in-typical Behrens-Fisher problem in general location-scale families.
We present a method of constructing generalized pivotal quantity (GPQ) and generalized P value (GPV) for the difference between two location parameters.
The suggested method is based on the minimum risk equivariant estimators (MREs), and thus, it is an extension of the methods based on maximum likelihood estimators and conditional inference, which have been, so far, applied to some specific distributions.
The efficiency of the procedure is illustrated by Monte Carlo simulation studies.
Finally, we apply the proposed method to two real datasets.
American Psychological Association (APA)
Nkurunziza, Sévérien& Chen, Fuqi. 2011. Equivariance and Generalized Inference in Two-Sample Location-Scale Families. Journal of Probability and Statistics،Vol. 2011, no. 2011, pp.1-16.
https://search.emarefa.net/detail/BIM-474460
Modern Language Association (MLA)
Nkurunziza, Sévérien& Chen, Fuqi. Equivariance and Generalized Inference in Two-Sample Location-Scale Families. Journal of Probability and Statistics No. 2011 (2011), pp.1-16.
https://search.emarefa.net/detail/BIM-474460
American Medical Association (AMA)
Nkurunziza, Sévérien& Chen, Fuqi. Equivariance and Generalized Inference in Two-Sample Location-Scale Families. Journal of Probability and Statistics. 2011. Vol. 2011, no. 2011, pp.1-16.
https://search.emarefa.net/detail/BIM-474460
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-474460