IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v133y2018icp15-22.html
   My bibliography  Save this article

The residual extropy of order statistics

Author

Listed:
  • Qiu, Guoxin
  • Jia, Kai

Abstract

Residual extropy was proposed to measure residual uncertainty of a random variable. Monotone properties and characterization results of this measure were studied. Similar properties of the proposed measure of order statistics were also discussed.

Suggested Citation

  • Qiu, Guoxin & Jia, Kai, 2018. "The residual extropy of order statistics," Statistics & Probability Letters, Elsevier, vol. 133(C), pages 15-22.
    • Handle: RePEc:eee:stapro:v:133:y:2018:i:c:p:15-22
    DOI: 10.1016/j.spl.2017.09.014
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167715217303085
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.spl.2017.09.014?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Qiu, Guoxin, 2017. "The extropy of order statistics and record values," Statistics & Probability Letters, Elsevier, vol. 120(C), pages 52-60.
    2. Furuichi, Shigeru & Mitroi, Flavia-Corina, 2012. "Mathematical inequalities for some divergences," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(1), pages 388-400.
    3. Park, Sangun, 1999. "A goodness-of-fit test for normality based on the sample entropy of order statistics," Statistics & Probability Letters, Elsevier, vol. 44(4), pages 359-363, October.
    4. Asadi, Majid & Ebrahimi, Nader, 2000. "Residual entropy and its characterizations in terms of hazard function and mean residual life function," Statistics & Probability Letters, Elsevier, vol. 49(3), pages 263-269, September.
    5. Gneiting, Tilmann & Raftery, Adrian E., 2007. "Strictly Proper Scoring Rules, Prediction, and Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 359-378, 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. Kayid, Mohamed, 2024. "Further results involving residual and past extropy with their applications," Statistics & Probability Letters, Elsevier, vol. 214(C).
    2. Nair, R. Dhanya & Sathar, E.I. Abdul, 2023. "Some useful results related to various measures of extropy and their interrelationship," Statistics & Probability Letters, Elsevier, vol. 193(C).
    3. Islam A. Husseiny & Metwally A. Alawady & Salem A. Alyami & Mohamed A. Abd Elgawad, 2023. "Measures of Extropy Based on Concomitants of Generalized Order Statistics under a General Framework from Iterated Morgenstern Family," Mathematics, MDPI, vol. 11(6), pages 1-17, March.
    4. Jose, Jitto & Abdul Sathar, E.I., 2019. "Residual extropy of k-record values," Statistics & Probability Letters, Elsevier, vol. 146(C), pages 1-6.
    5. Mohamed A. Abd Elgawad & Haroon M. Barakat & Metwally A. Alawady & Doaa A. Abd El-Rahman & Islam A. Husseiny & Atef F. Hashem & Naif Alotaibi, 2023. "Extropy and Some of Its More Recent Related Measures for Concomitants of K -Record Values in an Extended FGM Family," Mathematics, MDPI, vol. 11(24), pages 1-25, December.
    6. Kattumannil, Sudheesh K. & E.P., Sreedevi, 2022. "Non-parametric estimation of cumulative (residual) extropy," Statistics & Probability Letters, Elsevier, vol. 185(C).
    7. Radhakumari Maya & Archana Krishnakumar & Muhammed Rasheed Irshad & Christophe Chesneau, 2025. "Estimation of Weighted Extropy Under the α -Mixing Dependence Condition," Stats, MDPI, vol. 8(2), pages 1-18, May.
    8. M. Hashempour & M. Mohammadi & S. M. A. Jahanshahi & A. H. Khammar, 2024. "Modified Cumulative Extropies of Doubly Truncated Random Variables," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 86(2), pages 558-585, November.
    9. Morteza Mohammadi & Majid Hashempour, 2024. "On weighted version of dynamic cumulative residual inaccuracy measure based on extropy," Statistical Papers, Springer, vol. 65(7), pages 4599-4629, September.
    10. Majid Hashempour & Morteza Mohammadi & Osman Kamari, 2025. "On weighted version of dynamic residual inaccuracy measure using extropy in order statistics with applications in model selection," Statistical Papers, Springer, vol. 66(4), pages 1-28, June.

    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. Guoxin Qiu & Kai Jia, 2018. "Extropy estimators with applications in testing uniformity," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 30(1), pages 182-196, January.
    2. Kayid, Mohamed, 2024. "Further results involving residual and past extropy with their applications," Statistics & Probability Letters, Elsevier, vol. 214(C).
    3. Nitin Gupta & Santosh Kumar Chaudhary, 2024. "Some characterizations of continuous symmetric distributions based on extropy of record values," Statistical Papers, Springer, vol. 65(1), pages 291-308, February.
    4. Radhakumari Maya & Archana Krishnakumar & Muhammed Rasheed Irshad & Christophe Chesneau, 2025. "Estimation of Weighted Extropy Under the α -Mixing Dependence Condition," Stats, MDPI, vol. 8(2), pages 1-18, May.
    5. Saeed Hayati & Kenji Fukumizu & Afshin Parvardeh, 2024. "Kernel mean embedding of probability measures and its applications to functional data analysis," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 51(2), pages 447-484, June.
    6. Azar, Pablo D. & Micali, Silvio, 2018. "Computational principal agent problems," Theoretical Economics, Econometric Society, vol. 13(2), May.
    7. Luis A Barboza & Shu-Wei Chou-Chen & Paola Vásquez & Yury E García & Juan G Calvo & Hugo G Hidalgo & Fabio Sanchez, 2023. "Assessing dengue fever risk in Costa Rica by using climate variables and machine learning techniques," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 17(1), pages 1-13, January.
    8. Rubio, F.J. & Steel, M.F.J., 2011. "Inference for grouped data with a truncated skew-Laplace distribution," Computational Statistics & Data Analysis, Elsevier, vol. 55(12), pages 3218-3231, December.
    9. Basora, Luis & Viens, Arthur & Chao, Manuel Arias & Olive, Xavier, 2025. "A benchmark on uncertainty quantification for deep learning prognostics," Reliability Engineering and System Safety, Elsevier, vol. 253(C).
    10. R de Fondeville & A C Davison, 2018. "High-dimensional peaks-over-threshold inference," Biometrika, Biometrika Trust, vol. 105(3), pages 575-592.
    11. Domenico Piccolo & Rosaria Simone, 2019. "The class of cub models: statistical foundations, inferential issues and empirical evidence," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(3), pages 389-435, September.
    12. Finn Lindgren, 2015. "Comments on: Comparing and selecting spatial predictors using local criteria," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(1), pages 35-44, March.
    13. Chuliá, Helena & Garrón, Ignacio & Uribe, Jorge M., 2024. "Daily growth at risk: Financial or real drivers? The answer is not always the same," International Journal of Forecasting, Elsevier, vol. 40(2), pages 762-776.
    14. Kelly Trinh & Bo Zhang & Chenghan Hou, 2025. "Macroeconomic real‐time forecasts of univariate models with flexible error structures," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(1), pages 59-78, January.
    15. Laura Liu & Hyungsik Roger Moon & Frank Schorfheide, 2023. "Forecasting with a panel Tobit model," Quantitative Economics, Econometric Society, vol. 14(1), pages 117-159, January.
    16. Armantier, Olivier & Treich, Nicolas, 2013. "Eliciting beliefs: Proper scoring rules, incentives, stakes and hedging," European Economic Review, Elsevier, vol. 62(C), pages 17-40.
    17. Peysakhovich, Alexander & Plagborg-Møller, Mikkel, 2012. "A note on proper scoring rules and risk aversion," Economics Letters, Elsevier, vol. 117(1), pages 357-361.
    18. Merkle, Edgar C. & Steyvers, Mark & Mellers, Barbara & Tetlock, Philip E., 2017. "A neglected dimension of good forecasting judgment: The questions we choose also matter," International Journal of Forecasting, Elsevier, vol. 33(4), pages 817-832.
    19. Remy Elbez & Jeff Folz & Alan McLean & Hernan Roca & Joseph M Labuz & Kenneth J Pienta & Shuichi Takayama & Raoul Kopelman, 2021. "Cell-morphodynamic phenotype classification with application to cancer metastasis using cell magnetorotation and machine-learning," PLOS ONE, Public Library of Science, vol. 16(11), pages 1-14, November.
    20. Antonio Di Crescenzo & Patrizia Di Gironimo, 2018. "Stochastic Comparisons and Dynamic Information of Random Lifetimes in a Replacement Model," Mathematics, MDPI, vol. 6(10), pages 1-13, October.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:133:y:2018:i:c:p:15-22. 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.