Two Bootstrap Strategies for a k -Problem up to Location-Scale with Dependent Samples
Joint Authors
Quessy, Jean-François
Éthier, François
Source
Journal of Probability and Statistics
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-07-13
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
This paper extends the work of Quessy and Éthier (2012) who considered tests for the k -sample problem with dependent samples.
Here, the marginal distributions are allowed, under H 0 , to differ according to their mean and their variance; in other words, one focuses on the shape of the distributions.
Although easily stated, this problem nevertheless requires a careful treatment for the computation of valid P values.
To this end, two bootstrap strategies based on the multiplier central limit theorem are proposed, both exploiting a representation of the test statistics in terms of a Hadamard differentiable functional.
This accounts for the fact that one works with empirically standardized data instead of the original observations.
Simulations reported show the nice sample properties of the method based on Cramér-von Mises and characteristic function type statistics.
The newly introduced tests are illustrated on the marginal distributions of the eight-dimensional Oil currency data set.
American Psychological Association (APA)
Quessy, Jean-François& Éthier, François. 2014. Two Bootstrap Strategies for a k -Problem up to Location-Scale with Dependent Samples. Journal of Probability and Statistics،Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1042822
Modern Language Association (MLA)
Quessy, Jean-François& Éthier, François. Two Bootstrap Strategies for a k -Problem up to Location-Scale with Dependent Samples. Journal of Probability and Statistics No. 2014 (2014), pp.1-12.
https://search.emarefa.net/detail/BIM-1042822
American Medical Association (AMA)
Quessy, Jean-François& Éthier, François. Two Bootstrap Strategies for a k -Problem up to Location-Scale with Dependent Samples. Journal of Probability and Statistics. 2014. Vol. 2014, no. 2014, pp.1-12.
https://search.emarefa.net/detail/BIM-1042822
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1042822