BazEkon - The Main Library of the Cracow University of Economics

BazEkon home page

Main menu

Author
Pekasiewicz Dorota (University of Lodz, Poland)
Title
Interval Estimation of Higher Order Quantiles : Analysis of Accuracy of Selected Procedures
Source
Statistics in Transition, 2016, vol. 17, nr 4, s. 737-748, tab., wykr., bibliogr. s. 748
Keyword
Estymacja nieparametryczna, Analiza wartości zagrożonej, Statystyka, Metody samowsporne
Nonparametric estimation, Value at Risk Analysis, Statistics, Bootstrap
Note
summ.
Materiały z konferencji Multivariate Statistical Analysis 2015, Łódź
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. (original abstract)
Accessibility
The Main Library of the Cracow University of Economics
The Library of Warsaw School of Economics
The Library of University of Economics in Katowice
Full text
Show
Bibliography
Show
  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.
  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.
  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.
  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.
  7. ZIELIŃSKI, R, ZIELIŃSKI, W., (2005). Best Exact Nonparametric Confidence Intervals for Quantiles, Statistics, 34, pp. 353-355.
  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.
Cited by
Show
ISSN
1234-7655
Language
eng
Share on Facebook Share on Twitter Share on Google+ Share on Pinterest Share on LinkedIn Wyślij znajomemu