Simultaneous semi-sequential testing of dual alternatives for pattern recognition
In this paper, we propose a new nonparametric simultaneous test for dual alternatives. Simultaneous tests for dual alternatives are used for pattern detection of <italic>arsenic contamination</italic> level in ground water. We consider two possible patterns, namely, monotone shift and an umbrella-type location alternative, as the dual alternatives. Pattern recognition problems of this nature are addressed in Bandyopadhyay <italic>et al.</italic> [5], stretching the idea of multiple hypotheses tests as in Benjamini and Hochberg [6]. In the present context, we develop an alternative approach based on contrasts that helps us to detect three underlying pattern much more efficiently. We illustrate the new methodology through a motivating example related to highly sensitive issue of <italic>arsenic contamination</italic> in ground water. We provide some Monte-Carlo studies related to the proposed technique and give a comparative study between different detection procedures. We also obtain some related asymptotic results.
Year of publication: |
2011
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Authors: | Mukherjee, Amitava ; Purkait, Barendra |
Published in: |
Journal of Applied Statistics. - Taylor & Francis Journals, ISSN 0266-4763. - Vol. 38.2011, 2, p. 399-419
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Publisher: |
Taylor & Francis Journals |
Saved in:
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