Proceedings of the 2015 Conference on Informatization in Education, Management and Business

Parameter Estimation for Geometric-Gumbel Compound Extreme-value Distribution based on the pi-th Quantiles of Samples

Authors
Guan Qingsong, Peng Wei
Corresponding Author
Guan Qingsong
Available Online September 2015.
DOI
10.2991/iemb-15.2015.12How to use a DOI?
Keywords
Geometric-Gumbel Compound Extreme-value Distribution; Sample Quantile; Asymptotic Confidence Interval
Abstract

In this paper, the pi-th quantiles of samples on parameter estimation were applied to geometric-Gumbel compound extreme-value distribution. The asymptotic normal estimation of distribution parameter and scale parameter was proposed by linear regression model, based on k pi-th quantiles of extreme-value distribution simple sample. The asymptotic confidence interval was given for extreme-value distribution. Then, the effect was evaluated by numerical simulation, the result was good.

Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2015 Conference on Informatization in Education, Management and Business
Series
Advances in Social Science, Education and Humanities Research
Publication Date
September 2015
ISBN
978-94-6252-105-6
ISSN
2352-5398
DOI
10.2991/iemb-15.2015.12How to use a DOI?
Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Guan Qingsong
AU  - Peng Wei
PY  - 2015/09
DA  - 2015/09
TI  - Parameter Estimation for Geometric-Gumbel Compound Extreme-value Distribution based on the pi-th Quantiles of Samples
BT  - Proceedings of the 2015 Conference on Informatization in Education, Management and Business
PB  - Atlantis Press
SP  - 60
EP  - 64
SN  - 2352-5398
UR  - https://doi.org/10.2991/iemb-15.2015.12
DO  - 10.2991/iemb-15.2015.12
ID  - Qingsong2015/09
ER  -