INTERVAL ESTIMATION OF HIGHER ORDER QUANTILES. ANALYSIS OF ACCURACY OF SELECTED PROCEDURES

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Statistics in Transition New Series

Polish Statistical Association

Central Statistical Office of Poland

Subject: Economics, Statistics & Probability

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ISSN: 1234-7655
eISSN: 2450-0291

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VOLUME 17 , ISSUE 4 (December 2016) > List of articles

INTERVAL ESTIMATION OF HIGHER ORDER QUANTILES. ANALYSIS OF ACCURACY OF SELECTED PROCEDURES

Dorota Pekasiewicz *

Keywords : accuracy of estimation, order statistic, percentile bootstrap method, quantile, semiparametric bootstrap method, Value at Risk

Citation Information : Statistics in Transition New Series. Volume 17, Issue 4, Pages 737-748, DOI: https://doi.org/10.21307/stattrans-2016-049

License : (CC BY 4.0)

Published Online: 06-July-2017

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ABSTRACT

In the paper selected nonparametric and semiparametric estimation methods of higher orders quantiles are considered. The construction of nonparametric confidence intervals is based on order statistics of appropriate ranks from random samples or from generated bootstrap samples. Semiparametric bootstrap methods are characterized by double bootstrap simulations. The values of bootstrap sample below the prearranged threshold are generated by the empirical distribution and the values above this threshold are generated by the distribution based on the asymptotic properties of the tail of the random variable distribution. The results of the study allow one to draw conclusions about the effectiveness of the considered procedures and to compare these methods.

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REFERENCES

  1. DOMAŃSKI, C., PRUSKA, K., (2000). Nieklasyczne metody statystyczne, [Non-classical Statistical Methods], Polskie Wydawnictwo Ekonomiczne, Warszawa.
  2. EFRON, B., TIBSHIRANI, R. J., (1993), An Introduction to the Bootstrap, Chapman & Hall, New York.
  3. HUANG, M. L., BRILL, P. H., (1999). A Level Crossing Quantile Estimation Method, Statistics & Probability Letters, 45, pp. 111–119.
    [CROSSREF]
  4. LANDWEHR, J. M., MATALAS, N. C., WALLIS, J. R., (1979). Probability Weighted Moments Compared with Some Traditional Techniques in Estimating Gumbel Parameters and Quantiles, Water Resources Research 15(5), pp. 1055–1064.
    [CROSSREF]
  5. PANDEY, M. D., VAN GELDER, P. H. A. J. M., VRIJLING, J. K., (2003). Bootstrap Simulations for Evaluating the Uncertainty Associated with Peaks-over-Threshold Estimates of Extreme Wind Velocity, Environmetrics, 14, pp. 27–43.
    [CROSSREF]
  6. PEKASIEWICZ, D. (2015). Statystyki pozycyjne w procedurach estymacji i ich zastosowania w badaniach społeczno-ekonomicznych, [Order Statistics in Estimation Procedures and their Applications in Economic Research], Wydawnictwo Uniwersytetu Łódzkiego, Łódź.
    [CROSSREF]
  7. ZIELIŃSKI, R, ZIELIŃSKI, W., (2005). Best Exact Nonparametric Confidence Intervals for Quantiles, Statistics, 34, pp. 353–355.
    [CROSSREF]
  8. ZIELIŃSKI, W., (2008). Przykład zastosowania dokładnego nieparametrycznego przedziału ufności dla VaR, [Example of Application of Exact Nonparametric Interval Confidence for VaR] Metody Ilościowe w Badaniach Ekonomicznych, 9, pp. 239–244.
    [CROSSREF]
  9.  

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