Dorota Pekasiewicz
ARTICLE

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ABSTRACT

Quantile methods are used for estimation of population parameters when other methods such as the maximum likelihood method and the method of moments cannot be applied. In the paper the percentile method, the quantile least squares method and its two modifications are considered. The proposed methods allow estimators to be obtained with smaller bias and smaller mean squared error than estimators of the quantile least squares method. The considered methods can be applied to estimation of the Cauchy distribution parameters. The results of the simulation analysis of the estimator properties have allowed conclusions to be drawn as concerning the application of the considered methods.

KEYWORDS

quantile , percentile method, quantile least square method, Cauchy distribution

REFERENCES

AITCHISON, J., BROWN, J. A. C., (1975). The lognormal distribution. Cambridge University Press, Cambridge.

CASTILLO, E., HADI, A. S., BALAKRISHNAN, N., SARABIA, J. M., (2004). Extreme value and related models with application in engineering and science. Wiley Interscience, A. John Wiley & Sons, Inc. New Jersey.

GILCHRIST, W. G., (2000). Statistical modelling with quantile functions. Chapman & Hall/CRT, Boca Raton.

PEKASIEWICZ, D., (2012). The use of simulation methods to study the properties of estimators obtained by quantile method, [in:] collective work edited by Z. E. Zielinski: „The role of information technology in economic and social sciences. Innovations and interdisciplinary implications”. Publishing House of Higher School of Commerce, 236–244.

WYWIAŁ, J., (2004). Introduction to statistical inference. Publishing House of University of Economics in Katowice, Katowice

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