Empirical Bayes One-side Test for Inverse Exponential Model based on Negative Associate Samples

Guobing Fan

doi:doi:10.11648/j.ajtas.20160506.12

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Empirical Bayes One-side Test for Inverse Exponential Model based on Negative Associate Samples

Guobing Fan

Published in American Journal of Theoretical and Applied Statistics (Volume 5, Issue 6)

Received: 5 September 2016 Accepted: 23 September 2016 Published: 15 October 2016

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Abstract

By using the kernel-type density estimation and empirical distribution function in the case of identically distributed and negatively associated samples, the empirical Bayes one-sided test rules for the parameter of inverse exponential distribution are constructed based on negative associate sample under weighted linear loss function, and the asymptotically optimal property is obtained . It is shown that the convergence rates of the proposed empirical Bayes test rules can arbitrarily close to O(n^-1/2) under suitable conditions.

Published in	American Journal of Theoretical and Applied Statistics (Volume 5, Issue 6)
DOI	10.11648/j.ajtas.20160506.12
Page(s)	342-347
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2016. Published by Science Publishing Group

Keywords

Empirical Bayes test, Negatively Associated Sample, Asymptotic Optimality, Weighted Linear Loss Function, Inverse Exponential Distribution

References

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APA Style

Guobing Fan. (2016). Empirical Bayes One-side Test for Inverse Exponential Model based on Negative Associate Samples. American Journal of Theoretical and Applied Statistics, 5(6), 342-347. https://doi.org/10.11648/j.ajtas.20160506.12

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ACS Style

Guobing Fan. Empirical Bayes One-side Test for Inverse Exponential Model based on Negative Associate Samples. Am. J. Theor. Appl. Stat. 2016, 5(6), 342-347. doi: 10.11648/j.ajtas.20160506.12

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AMA Style

Guobing Fan. Empirical Bayes One-side Test for Inverse Exponential Model based on Negative Associate Samples. Am J Theor Appl Stat. 2016;5(6):342-347. doi: 10.11648/j.ajtas.20160506.12

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@article{10.11648/j.ajtas.20160506.12,
  author = {Guobing Fan},
  title = {Empirical Bayes One-side Test for Inverse Exponential Model based on Negative Associate Samples},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {5},
  number = {6},
  pages = {342-347},
  doi = {10.11648/j.ajtas.20160506.12},
  url = {https://doi.org/10.11648/j.ajtas.20160506.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20160506.12},
  abstract = {By using the kernel-type density estimation and empirical distribution function in the case of identically distributed and negatively associated samples, the empirical Bayes one-sided test rules for the parameter of inverse exponential distribution are constructed based on negative associate sample under weighted linear loss function, and the asymptotically optimal property is obtained . It is shown that the convergence rates of the proposed empirical Bayes test rules can arbitrarily close to O(n-1/2) under suitable conditions.},
 year = {2016}
}

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TY  - JOUR
T1  - Empirical Bayes One-side Test for Inverse Exponential Model based on Negative Associate Samples
AU  - Guobing Fan
Y1  - 2016/10/15
PY  - 2016
N1  - https://doi.org/10.11648/j.ajtas.20160506.12
DO  - 10.11648/j.ajtas.20160506.12
T2  - American Journal of Theoretical and Applied Statistics
JF  - American Journal of Theoretical and Applied Statistics
JO  - American Journal of Theoretical and Applied Statistics
SP  - 342
EP  - 347
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20160506.12
AB  - By using the kernel-type density estimation and empirical distribution function in the case of identically distributed and negatively associated samples, the empirical Bayes one-sided test rules for the parameter of inverse exponential distribution are constructed based on negative associate sample under weighted linear loss function, and the asymptotically optimal property is obtained . It is shown that the convergence rates of the proposed empirical Bayes test rules can arbitrarily close to O(n-1/2) under suitable conditions.
VL  - 5
IS  - 6
ER  -

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Author Information

Guobing Fan

Department of Basic Subjects, Hunan University of Finance and Economics, Changsha, China

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APA Style

Guobing Fan. (2016). Empirical Bayes One-side Test for Inverse Exponential Model based on Negative Associate Samples. American Journal of Theoretical and Applied Statistics, 5(6), 342-347. https://doi.org/10.11648/j.ajtas.20160506.12

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ACS Style

Guobing Fan. Empirical Bayes One-side Test for Inverse Exponential Model based on Negative Associate Samples. Am. J. Theor. Appl. Stat. 2016, 5(6), 342-347. doi: 10.11648/j.ajtas.20160506.12

Copy | Download

AMA Style

Guobing Fan. Empirical Bayes One-side Test for Inverse Exponential Model based on Negative Associate Samples. Am J Theor Appl Stat. 2016;5(6):342-347. doi: 10.11648/j.ajtas.20160506.12

Copy | Download

@article{10.11648/j.ajtas.20160506.12,
  author = {Guobing Fan},
  title = {Empirical Bayes One-side Test for Inverse Exponential Model based on Negative Associate Samples},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {5},
  number = {6},
  pages = {342-347},
  doi = {10.11648/j.ajtas.20160506.12},
  url = {https://doi.org/10.11648/j.ajtas.20160506.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20160506.12},
  abstract = {By using the kernel-type density estimation and empirical distribution function in the case of identically distributed and negatively associated samples, the empirical Bayes one-sided test rules for the parameter of inverse exponential distribution are constructed based on negative associate sample under weighted linear loss function, and the asymptotically optimal property is obtained . It is shown that the convergence rates of the proposed empirical Bayes test rules can arbitrarily close to O(n-1/2) under suitable conditions.},
 year = {2016}
}

Copy | Download

TY  - JOUR
T1  - Empirical Bayes One-side Test for Inverse Exponential Model based on Negative Associate Samples
AU  - Guobing Fan
Y1  - 2016/10/15
PY  - 2016
N1  - https://doi.org/10.11648/j.ajtas.20160506.12
DO  - 10.11648/j.ajtas.20160506.12
T2  - American Journal of Theoretical and Applied Statistics
JF  - American Journal of Theoretical and Applied Statistics
JO  - American Journal of Theoretical and Applied Statistics
SP  - 342
EP  - 347
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20160506.12
AB  - By using the kernel-type density estimation and empirical distribution function in the case of identically distributed and negatively associated samples, the empirical Bayes one-sided test rules for the parameter of inverse exponential distribution are constructed based on negative associate sample under weighted linear loss function, and the asymptotically optimal property is obtained . It is shown that the convergence rates of the proposed empirical Bayes test rules can arbitrarily close to O(n-1/2) under suitable conditions.
VL  - 5
IS  - 6
ER  -

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