IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v95y2014icp110-117.html
   My bibliography  Save this article

A generalized boxplot for skewed and heavy-tailed distributions

Author

Listed:
  • Bruffaerts, Christopher
  • Verardi, Vincenzo
  • Vermandele, Catherine

Abstract

We define a new boxplot that can deal with skewed and/or heavy-tailed distributions and possible outliers. The methodology relies on a rank-preserving transformation that allows to fit a so-called Tukey g -and-h distribution.

Suggested Citation

  • Bruffaerts, Christopher & Verardi, Vincenzo & Vermandele, Catherine, 2014. "A generalized boxplot for skewed and heavy-tailed distributions," Statistics & Probability Letters, Elsevier, vol. 95(C), pages 110-117.
  • Handle: RePEc:eee:stapro:v:95:y:2014:i:c:p:110-117
    DOI: 10.1016/j.spl.2014.08.016
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167715214002971
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.spl.2014.08.016?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Hubert, M. & Vandervieren, E., 2008. "An adjusted boxplot for skewed distributions," Computational Statistics & Data Analysis, Elsevier, vol. 52(12), pages 5186-5201, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Christophe Muller & Nouréini Sayouti, 2019. "How Do Agro-Pastoral Policies Affect the Dietary Intake of Agro-Pastoralists? Evidence from Niger," AMSE Working Papers 1917, Aix-Marseille School of Economics, France, revised Apr 2020.
    2. Safari, Muhammad Aslam Mohd & Masseran, Nurulkamal & Ibrahim, Kamarulzaman & AL-Dhurafi, Nasr Ahmed, 2020. "The power-law distribution for the income of poor households," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 557(C).
    3. Vincenzo Verardi, 2013. "Semiparametric regression in Stata," United Kingdom Stata Users' Group Meetings 2013 14, Stata Users Group.
    4. Muhammad Aslam Mohd Safari & Nurulkamal Masseran & Muhammad Hilmi Abdul Majid, 2020. "Robust Reliability Estimation for Lindley Distribution—A Probability Integral Transform Statistical Approach," Mathematics, MDPI, vol. 8(9), pages 1-21, September.
    5. Silvia De Nicol`o & Maria Rosaria Ferrante & Silvia Pacei, 2021. "Mind the Income Gap: Bias Correction of Inequality Estimators in Small-Sized Samples," Papers 2107.08950, arXiv.org, revised May 2023.
    6. repec:hal:cdiwps:halshs-02532955 is not listed on IDEAS
    7. Funke, Benedikt & Hirukawa, Masayuki, 2021. "Bias correction for local linear regression estimation using asymmetric kernels via the skewing method," Econometrics and Statistics, Elsevier, vol. 20(C), pages 109-130.
    8. Safari, Muhammad Aslam Mohd & Masseran, Nurulkamal & Ibrahim, Kamarulzaman & Hussain, Saiful Izzuan, 2021. "Measuring income inequality: A robust semi-parametric approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 562(C).
    9. Ghesla, Claus & Grieder, Manuel & Schmitz, Jan & Stadelmann, Marcel, 2020. "Pro-environmental incentives and loss aversion: A field experiment on electricity saving behavior," Energy Policy, Elsevier, vol. 137(C).
    10. Çevik, Emre & Çevik, Emrah İsmail & Dibooglu, Sel & Cergibozan, Raif & Bugan, Mehmet Fatih & Destek, Mehmet Akif, 2022. "Connectedness and risk spillovers between crude oil and clean energy stock markets," MPRA Paper 117558, University Library of Munich, Germany.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mia Hubert & Peter Rousseeuw & Pieter Segaert, 2015. "Multivariate functional outlier detection," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(2), pages 177-202, July.
    2. Nicodemo, Catia & Satorra, Albert, 2020. "Exploratory Data Analysis on Large Data Sets: The Example of Salary Variation in Spanish Social Security Data," IZA Discussion Papers 13459, Institute of Labor Economics (IZA).
    3. Warshaw, Evan, 2020. "Asymmetric volatility spillover between European equity and foreign exchange markets: Evidence from the frequency domain," International Review of Economics & Finance, Elsevier, vol. 68(C), pages 1-14.
    4. Vincenzo Verardi, 2013. "Semiparametric regression in Stata," United Kingdom Stata Users' Group Meetings 2013 14, Stata Users Group.
    5. Finger, Robert, 2012. "Biases in Farm-Level Yield Risk Analysis due to Data Aggregation," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 61(01), pages 1-14, February.
    6. Shirin Enshaeifar & Ahmed Zoha & Andreas Markides & Severin Skillman & Sahr Thomas Acton & Tarek Elsaleh & Masoud Hassanpour & Alireza Ahrabian & Mark Kenny & Stuart Klein & Helen Rostill & Ramin Nilf, 2018. "Health management and pattern analysis of daily living activities of people with dementia using in-home sensors and machine learning techniques," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-20, May.
    7. Mario A. Rojas & Yuri A. Iriarte, 2022. "A Lindley-Type Distribution for Modeling High-Kurtosis Data," Mathematics, MDPI, vol. 10(13), pages 1-19, June.
    8. Maciej Kostrzewski & Jadwiga Kostrzewska, 2021. "The Impact of Forecasting Jumps on Forecasting Electricity Prices," Energies, MDPI, vol. 14(2), pages 1-17, January.
    9. Václav Plevka & Pieter Segaert & Chris M. J. Tampère & Mia Hubert, 2016. "Analysis of travel activity determinants using robust statistics," Transportation, Springer, vol. 43(6), pages 979-996, November.
    10. V�ctor Leiva & Emilia Athayde & Cecilia Azevedo & Carolina Marchant, 2011. "Modeling wind energy flux by a Birnbaum--Saunders distribution with an unknown shift parameter," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(12), pages 2819-2838, February.
    11. M. Hubert & P. Rousseeuw & K. Vakili, 2014. "Shape bias of robust covariance estimators: an empirical study," Statistical Papers, Springer, vol. 55(1), pages 15-28, February.
    12. Jeremias Leão & Francisco Cysneiros & Helton Saulo & N. Balakrishnan, 2016. "Constrained test in linear models with multivariate power exponential distribution," Computational Statistics, Springer, vol. 31(4), pages 1569-1592, December.
    13. Alvarez, Agustín & Boente, Graciela & Kudraszow, Nadia, 2019. "Robust sieve estimators for functional canonical correlation analysis," Journal of Multivariate Analysis, Elsevier, vol. 170(C), pages 46-62.
    14. Francesca Ieva & Anna Maria Paganoni, 2020. "Component-wise outlier detection methods for robustifying multivariate functional samples," Statistical Papers, Springer, vol. 61(2), pages 595-614, April.
    15. Bourguignon, Marcelo & Saulo, Helton & Fernandez, Rodrigo Nobre, 2016. "A new Pareto-type distribution with applications in reliability and income data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 166-175.
    16. Hervé Cardot & Antonio Musolesi, 2018. "Modeling temporal treatment effects with zero inflated semi-parametric regression models: the case of local development policies in France," SEEDS Working Papers 0718, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Mar 2018.
    17. Danúbia R. Cunha & Roberto Vila & Helton Saulo & Rodrigo N. Fernandez, 2020. "A General Family of Autoregressive Conditional Duration Models Applied to High-Frequency Financial Data," JRFM, MDPI, vol. 13(3), pages 1-20, March.
    18. Trobia, José & de Souza, Silvio L.T. & dos Santos, Margarete A. & Szezech, José D. & Batista, Antonio M. & Borges, Rafael R. & Pereira, Leandro da S. & Protachevicz, Paulo R. & Caldas, Iberê L. & Iaro, 2022. "On the dynamical behaviour of a glucose-insulin model," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    19. Heesche, Emil & Asmild, Mette, 2022. "Incorporating quality in economic regulatory benchmarking," Omega, Elsevier, vol. 110(C).
    20. Peter Congdon, 2017. "Quantile regression for overdispersed count data: a hierarchical method," Journal of Statistical Distributions and Applications, Springer, vol. 4(1), pages 1-19, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:stapro:v:95:y:2014:i:c:p:110-117. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.