IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v111y2016icp18-25.html
   My bibliography  Save this article

Quality of fit measurement in regression quantiles: An elemental set method approach

Author

Listed:
  • Ranganai, Edmore

Abstract

Little attention has been paid to assess the quality of fit in the quantile regression framework (Noh et al., 2013). As a contribution, I propose a coefficient of determination measure and model selection indices based on the elemental set method.

Suggested Citation

  • Ranganai, Edmore, 2016. "Quality of fit measurement in regression quantiles: An elemental set method approach," Statistics & Probability Letters, Elsevier, vol. 111(C), pages 18-25.
    • Handle: RePEc:eee:stapro:v:111:y:2016:i:c:p:18-25
    DOI: 10.1016/j.spl.2015.12.018
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167715215004010
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.spl.2015.12.018?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. Edmore Ranganai & Johan O. Van Vuuren & Tertius De Wet, 2014. "Multiple Case High Leverage Diagnosis in Regression Quantiles," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 43(16), pages 3343-3370, August.
    2. Noh, Hohsuk & El Ghouch, Anouar & Van Keilegom, Ingrid, 2013. "Quality of fit measures in the framework of quantile regression," LIDAM Reprints ISBA 2013010, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    3. McKean, Joseph W. & Sievers, Gerald L., 1987. "Coefficients of determination for least absolute deviation analysis," Statistics & Probability Letters, Elsevier, vol. 5(1), pages 49-54, January.
    4. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    5. Hohsuk Noh & Anouar El Ghouch & Ingrid Van Keilegom, 2013. "Quality of Fit Measures in the Framework of Quantile Regression," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 40(1), pages 105-118, March.
    6. Hawkins, Douglas M. & Olive, David J., 1999. "Improved feasible solution algorithms for high breakdown estimation," Computational Statistics & Data Analysis, Elsevier, vol. 30(1), pages 1-11, March.
    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. Paulino José García Nieto & Esperanza García-Gonzalo & Antonio Bernardo Sánchez & Marta Menéndez Fernández, 2016. "A New Predictive Model Based on the ABC Optimized Multivariate Adaptive Regression Splines Approach for Predicting the Remaining Useful Life in Aircraft Engines," Energies, MDPI, vol. 9(6), pages 1-19, May.

    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. Noh, Hohsuk & El Ghouch, Anouar & Van Keilegom, Ingrid, 2013. "Assessing model adequacy in possibly misspecified quantile regression," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 558-569.
    2. Alfonso Carfora & Monica Ronghi & Giuseppe Scandurra, 2017. "The effect of Climate Finance on Greenhouse Gas Emission: A Quantile Regression Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 7(1), pages 185-199.
    3. Noh, Hohsuk & El Ghouch, Anouar & Van Keilegom, Ingrid, 2011. "On assessing model adequacy in linear quantile regression," LIDAM Discussion Papers ISBA 2011024, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    4. Akosah, Nana Kwame & Alagidede, Imhotep Paul & Schaling, Eric, 2020. "Testing for asymmetry in monetary policy rule for small-open developing economies: Multiscale Bayesian quantile evidence from Ghana," The Journal of Economic Asymmetries, Elsevier, vol. 22(C).
    5. Molyneux, Philip & Pancotto, Livia & Reghezza, Alessio & Rodriguez d'Acri, Costanza, 2022. "Interest rate risk and monetary policy normalisation in the euro area," Journal of International Money and Finance, Elsevier, vol. 124(C).
    6. Paul Hewson & Keming Yu, 2008. "Quantile regression for binary performance indicators," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 24(5), pages 401-418, September.
    7. Georgios Bertsatos & Plutarchos Sakellaris & Mike G. Tsionas, 2022. "Extensions of the Pesaran, Shin and Smith (2001) bounds testing procedure," Empirical Economics, Springer, vol. 62(2), pages 605-634, February.
    8. Salimata Sissoko, 2011. "Working Paper 03-11 - Niveau de décentralisation de la négociation et structure des salaires," Working Papers 1103, Federal Planning Bureau, Belgium.
    9. Korom, Philipp, 2016. "Inherited advantage: The importance of inheritance for private wealth accumulation in Europe," MPIfG Discussion Paper 16/11, Max Planck Institute for the Study of Societies.
    10. Daniele, Vittorio, 2007. "Criminalità e investimenti esteri. Un’analisi per le province italiane [The effect of organized crime on Foreign Investments. An Empirical Analysis for the Italian Provinces]," MPRA Paper 6417, University Library of Munich, Germany.
    11. Ma, Lingjie & Koenker, Roger, 2006. "Quantile regression methods for recursive structural equation models," Journal of Econometrics, Elsevier, vol. 134(2), pages 471-506, October.
    12. Cuesta, Lizeth & Ruiz, Yomara, 2021. "Efecto de la globalización sobre la desigualdad. Un estudio global para 104 países usando regresiones cuantílicas [Effect of globalization on inequality. A global study for 104 countries using quan," MPRA Paper 111022, University Library of Munich, Germany.
    13. Dutta, Anupam & Bouri, Elie & Rothovius, Timo & Uddin, Gazi Salah, 2023. "Climate risk and green investments: New evidence," Energy, Elsevier, vol. 265(C).
    14. Cowling, Marc & Ughetto, Elisa & Lee, Neil, 2018. "The innovation debt penalty: Cost of debt, loan default, and the effects of a public loan guarantee on high-tech firms," Technological Forecasting and Social Change, Elsevier, vol. 127(C), pages 166-176.
    15. Guili Liao & Qimeng Liu & Rongmao Zhang & Shifang Zhang, 2022. "Rank test of unit‐root hypothesis with AR‐GARCH errors," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(5), pages 695-719, September.
    16. Shweta Bahl & Ajay Sharma, 2021. "Education–Occupation Mismatch and Dispersion in Returns to Education: Evidence from India," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 153(1), pages 251-298, January.
    17. Nguyen, Thao & Bai, Min & Hou, Greg & Vu, Manh-Chien, 2020. "State ownership and adjustment speed toward target leverage: Evidence from a transitional economy," Research in International Business and Finance, Elsevier, vol. 53(C).
    18. Asongu, Simplice A. & Odhiambo, Nicholas M., 2021. "Inequality, finance and renewable energy consumption in Sub-Saharan Africa," Renewable Energy, Elsevier, vol. 165(P1), pages 678-688.
    19. Kemp, Gordon C.R. & Santos Silva, J.M.C., 2012. "Regression towards the mode," Journal of Econometrics, Elsevier, vol. 170(1), pages 92-101.
    20. Niematallah Elamin & Mototsugu Fukushige, 2016. "A Quantile Regression Model for Electricity Peak Demand Forecasting: An Approach to Avoiding Power Blackouts," Discussion Papers in Economics and Business 16-22, Osaka University, Graduate School of Economics.

    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:111:y:2016:i:c:p:18-25. 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.