Probabilities for asymmetric p-outside values
DOI:
https://doi.org/10.55630/mem.2025.54.051-060Keywords:
heavy-tailed distributions, extremal index estimationAbstract
Since 2017, Jordanova and co-authors investigate probabilities for p-outside values and determine their explicit forms in many particular cases. They show that they are closely related to the concept of heavy tails. Tukey’s box-plots are very popular and useful in practice. In particular, the relative frequencies for observing a data point in different sections of the box-plot can help practitioners find the exact probability distribution of the underlying random variable. These open the door to working with distribution-sensitive estimators, which can be more accurate, especially in small sample investigations. All these methods, however, suffer from the drawback that they use the interquantile range in a symmetric way. This study gives greater influence on asymmetry in the analysis of the tails of distributions. New theoretical and empirical box-plots and characteristics of the tails of distributions are suggested. The theoretical asymmetric p-outside value functions do not depend on the center and scaling factor of the distribution and do not need existence of moments. Therefore, they are appropriate for comparing the tails of distributions and for estimating the parameters that govern their tail behaviour.
References
J.L. DeVore. Probability and Statistics for Engineering and the Sciences. Brooks/Cole Publishing Company, 1995.
R.J. Hyndman, Y. Fan. Sample quantiles in statistical packages. Am. Stat., 50 (1996), 361–365.
P.K. Jordanova. Probabilities for p-outside values – General properties. AIP Conf. Proc., 2164 (2019), article no. 020002.
P.K. Jordanova. Probabilities for p-outside values – Particular cases. AIP Conf. Proc., 2172 (2019), article no. 100004.
P.K. Jordanova. Probabilities for p-Outside Values and Heavy Tails. Konstantin Preslavsky Publishing House, Shumen, 2020.
P.K. Jordanova, M.P. Petkova. Measuring heavy-tailedness of distributions.
AIP Conf. Proc., 1910 (2017), article no. 060002.
P.K. Jordanova, M.P. Petkova. Tails and probabilities for extreme outliers.
AIP Conf. Proc., 2025 (2018), article no. 030002.
R. McGill, J.W. Tukey, W.A. Larsen. Variations of box plots. Am. Stat., 32 (1978), 12–16.
R Core Team and others. R: A Language and Environment for Statistical Computing. Foundation for Statistical Computing, Vienna, Austria, 2013.
R.J. Serfling. Approximation Theorems of Mathematical Statistics. John Wiley & Sons, Inc., New York, 2009.
J.W. Tukey. Exploratory Data Analysis. Addison-Wesley Publishing Company, Reading, 1977.