IDEAS home Printed from https://ideas.repec.org/a/spr/stpapr/v61y2020i6d10.1007_s00362-018-1052-7.html
   My bibliography  Save this article

Estimating a function of scale parameter of an exponential population with unknown location under general loss function

Author

Listed:
  • Lakshmi Kanta Patra

    (Indian Institute of Petroleum and Energy)

  • Suchandan Kayal

    (National Institute of Technology Rourkela)

  • Somesh Kumar

    (Indian Institute of Technology Kharagpur)

Abstract

In the present study, we consider the problem of estimating a function of scale parameter $$\ln \sigma $$ ln σ under an arbitrary location invariant bowl-shaped loss function, when location parameter $$\mu $$ μ is unknown. Various improved estimators are proposed. Inadmissibility of the best affine equivariant estimator (BAEE) of $$\ln \sigma $$ ln σ is established by deriving a Stein-type estimator. This improved estimator is not smooth. We derive a smooth estimator improving upon the BAEE. Further, the integral expression of risk difference (IERD) approach of Kubokawa is used to derive a class of improved estimators. To illustrate these results, we consider two specific loss functions: squared error and linex loss functions, and derive various estimators improving upon the BAEE. Finally, a simulation study has been carried out to numerically compare the risk performance of the improved estimators.

Suggested Citation

  • Lakshmi Kanta Patra & Suchandan Kayal & Somesh Kumar, 2020. "Estimating a function of scale parameter of an exponential population with unknown location under general loss function," Statistical Papers, Springer, vol. 61(6), pages 2511-2527, December.
    • Handle: RePEc:spr:stpapr:v:61:y:2020:i:6:d:10.1007_s00362-018-1052-7
    DOI: 10.1007/s00362-018-1052-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00362-018-1052-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s00362-018-1052-7?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. Constantinos Petropoulos, 2017. "Estimation of the order restricted scale parameters for two populations from the Lomax distribution," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 80(4), pages 483-502, May.
    2. Misra, Neeraj & Singh, Harshinder & Demchuk, Eugene, 2005. "Estimation of the entropy of a multivariate normal distribution," Journal of Multivariate Analysis, Elsevier, vol. 92(2), pages 324-342, February.
    3. Mohd. Arshad & Neeraj Misra, 2016. "Estimation after selection from exponential populations with unequal scale parameters," Statistical Papers, Springer, vol. 57(3), pages 605-621, September.
    4. Kayal, Suchandan & Kumar, Somesh, 2013. "Estimation of the Shannon’s entropy of several shifted exponential populations," Statistics & Probability Letters, Elsevier, vol. 83(4), pages 1127-1135.
    5. Nader Nematollahi, 2017. "Admissible and minimax estimation of the parameter of the selected Pareto population under squared log error loss function," Statistical Papers, Springer, vol. 58(2), pages 319-339, June.
    6. Riyadh Rustam Al-Mosawi & Shahjahan Khan, 2018. "Estimating moments of a selected Pareto population under asymmetric scale invariant loss function," Statistical Papers, Springer, vol. 59(1), pages 183-198, March.
    7. Petr Jizba & Hagen Kleinert & Mohammad Shefaat, 2011. "Renyi's information transfer between financial time series," Papers 1106.5913, arXiv.org, revised Jan 2012.
    8. Jizba, Petr & Kleinert, Hagen & Shefaat, Mohammad, 2012. "Rényi’s information transfer between financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(10), pages 2971-2989.
    9. Panayiotis Bobotas & George Iliopoulos & Stavros Kourouklis, 2012. "Estimating the ratio of two scale parameters: a simple approach," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 64(2), pages 343-357, April.
    Full references (including those not matched with items on IDEAS)

    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. Dimpfl, Thomas & Peter, Franziska J., 2014. "The impact of the financial crisis on transatlantic information flows: An intraday analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 31(C), pages 1-13.
    2. Caferra, Rocco, 2022. "Sentiment spillover and price dynamics: Information flow in the cryptocurrency and stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    3. Nie, Chun-Xiao, 2023. "Time-varying characteristics of information flow networks in the Chinese market: An analysis based on sector indices," Finance Research Letters, Elsevier, vol. 54(C).
    4. Xiao, Di & Wang, Jun, 2020. "Dynamic complexity and causality of crude oil and major stock markets," Energy, Elsevier, vol. 193(C).
    5. Aslanidis, Nektarios & Bariviera, Aurelio F. & López, Óscar G., 2022. "The link between cryptocurrencies and Google Trends attention," Finance Research Letters, Elsevier, vol. 47(PA).
    6. Batra, Luckshay & Taneja, H.C., 2020. "Evaluating volatile stock markets using information theoretic measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    7. Lakshmi Kanta Patra & Suchandan Kayal & Somesh Kumar, 2021. "Minimax estimation of the common variance and precision of two normal populations with ordered restricted means," Statistical Papers, Springer, vol. 62(1), pages 209-233, February.
    8. Hassad de Andrade, Liz & Moreira Antunes, Jorge Junio & Araújo de Medeiros, Antônio Mamede & Wanke, Peter & Nunes, Bernardo Pereira, 2022. "The impact of social welfare and COVID-19 stringency on the perceived utility of food apps: A hybrid MCDM approach," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    9. Ferreira, Paulo & Almeida, Dora & Dionísio, Andreia & Bouri, Elie & Quintino, Derick, 2022. "Energy markets – Who are the influencers?," Energy, Elsevier, vol. 239(PA).
    10. Parthajit Kayal & Moinak Maiti, 2023. "Examining the asymmetric information flow between pairs of gold, silver, and oil: a transfer entropy approach," SN Business & Economics, Springer, vol. 3(10), pages 1-22, October.
    11. Banerjee, Ameet Kumar & Akhtaruzzaman, Md & Dionisio, Andreia & Almeida, Dora & Sensoy, Ahmet, 2022. "Nonlinear nexus between cryptocurrency returns and COVID-19 news sentiment," Journal of Behavioral and Experimental Finance, Elsevier, vol. 36(C).
    12. Theo Diamandis & Yonathan Murin & Andrea Goldsmith, 2018. "Ranking Causal Influence of Financial Markets via Directed Information Graphs," Papers 1801.06896, arXiv.org.
    13. Leonidas Sandoval Junior, 2014. "Dynamics in two networks based on stocks of the US stock market," Papers 1408.1728, arXiv.org, revised Aug 2014.
    14. Neto, David, 2021. "Are Google searches making the Bitcoin market run amok? A tail event analysis," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    15. Kayal, Suchandan & Kumar, Somesh, 2013. "Estimation of the Shannon’s entropy of several shifted exponential populations," Statistics & Probability Letters, Elsevier, vol. 83(4), pages 1127-1135.
    16. Neto, David, 2022. "Examining interconnectedness between media attention and cryptocurrency markets: A transfer entropy story," Economics Letters, Elsevier, vol. 214(C).
    17. Tatsuya Kubokawa, 2013. "General Dominance Properties of Double Shrinkage Estimators for Ratio of Positive Parameters," CIRJE F-Series CIRJE-F-901, CIRJE, Faculty of Economics, University of Tokyo.
    18. Dima, Bogdan & Dima, Ştefana Maria & Barna, Flavia, 2014. "The signaling effect of tax rates under fiscal competition: A (Shannonian) transfer entropy approach," Economic Modelling, Elsevier, vol. 42(C), pages 373-381.
    19. Withers, Christopher S. & Nadarajah, Saralees, 2011. "Estimates of low bias for the multivariate normal," Statistics & Probability Letters, Elsevier, vol. 81(11), pages 1635-1647, November.
    20. Mohammed S. Kotb & Huda M. Alomari, 2024. "Estimating the entropy of a Rayleigh model under progressive first-failure censoring," Statistical Papers, Springer, vol. 65(5), pages 3135-3154, July.

    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:spr:stpapr:v:61:y:2020:i:6:d:10.1007_s00362-018-1052-7. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.