IDEAS home Printed from https://ideas.repec.org/a/spr/stpapr/v53y2012i1p51-60.html
   My bibliography  Save this article

Bayesian and Robust Bayesian analysis under a general class of balanced loss functions

Author

Listed:
  • Mohammad Jafari Jozani
  • Éric Marchand
  • Ahmad Parsian

Abstract

No abstract is available for this item.

Suggested Citation

  • Mohammad Jafari Jozani & Éric Marchand & Ahmad Parsian, 2012. "Bayesian and Robust Bayesian analysis under a general class of balanced loss functions," Statistical Papers, Springer, vol. 53(1), pages 51-60, February.
    • Handle: RePEc:spr:stpapr:v:53:y:2012:i:1:p:51-60
    DOI: 10.1007/s00362-010-0307-8
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s00362-010-0307-8
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s00362-010-0307-8?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. James Berger & Elías Moreno & Luis Pericchi & M. Bayarri & José Bernardo & Juan Cano & Julián Horra & Jacinto Martín & David Ríos-Insúa & Bruno Betrò & A. Dasgupta & Paul Gustafson & Larry Wasserman &, 1994. "An overview of robust Bayesian analysis," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 3(1), pages 5-124, June.
    2. Jafari Jozani, Mohammad & Marchand, Éric & Parsian, Ahmad, 2006. "On estimation with weighted balanced-type loss function," Statistics & Probability Letters, Elsevier, vol. 76(8), pages 773-780, April.
    3. Dey, Dipak K. & Ghosh, Malay & Strawderman, William E., 1999. "On estimation with balanced loss functions," Statistics & Probability Letters, Elsevier, vol. 45(2), pages 97-101, November.
    4. Zen Mei-Mei & DasGupta A., 1993. "Estimating A Binomial Parameter: Is Robust Bayes Real Bayes?," Statistics & Risk Modeling, De Gruyter, vol. 11(1), pages 37-60, January.
    5. Heilmann, Wolf-Rudiger, 1989. "Decision theoretic foundations of credibility theory," Insurance: Mathematics and Economics, Elsevier, vol. 8(1), pages 77-95, March.
    6. Zellner, A., 1992. "Bayesian and Non-Bayesian Estimation using Balanced Loss Functions," Papers 92-20, California Irvine - School of Social Sciences.
    7. Meczarski, Marek & Zielinski, Ryszard, 1991. "Stability of the Bayesian estimator of the Poisson mean under the inexactly specified gamma prior," Statistics & Probability Letters, Elsevier, vol. 12(4), pages 329-333, October.
    8. H. Toutenburg & Shalabh, 2005. "Estimation of regression coefficients subject to exact linear restrictions when some observations are missing and quadratic error balanced loss function is used," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 14(2), pages 385-396, December.
    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. Cao, Ming-Xiang & He, Dao-Jiang, 2017. "Admissibility of linear estimators of the common mean parameter in general linear models under a balanced loss function," Journal of Multivariate Analysis, Elsevier, vol. 153(C), pages 246-254.
    2. Kyeongjun Lee & Youngseuk Cho, 2017. "Bayesian and maximum likelihood estimations of the inverted exponentiated half logistic distribution under progressive Type II censoring," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(5), pages 811-832, April.
    3. Mehrjoo, Mehrdad & Jafari Jozani, Mohammad & Pawlak, Miroslaw, 2021. "Toward hybrid approaches for wind turbine power curve modeling with balanced loss functions and local weighting schemes," Energy, Elsevier, vol. 218(C).
    4. Essam A. Ahmed, 2014. "Bayesian estimation based on progressive Type-II censoring from two-parameter bathtub-shaped lifetime model: an Markov chain Monte Carlo approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(4), pages 752-768, April.
    5. Marchand, Éric & Strawderman, William E., 2020. "On shrinkage estimation for balanced loss functions," Journal of Multivariate Analysis, Elsevier, vol. 175(C).
    6. Kousik Maiti & Suchandan Kayal, 2019. "Estimation for the generalized Fréchet distribution under progressive censoring scheme," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(5), pages 1276-1301, October.
    7. Karamikabir, Hamid & Afshari, Mahmoud, 2020. "Generalized Bayesian shrinkage and wavelet estimation of location parameter for spherical distribution under balance-type loss: Minimaxity and admissibility," Journal of Multivariate Analysis, Elsevier, vol. 177(C).
    8. Hobbad, Lahoucine & Marchand, Éric & Ouassou, Idir, 2021. "On shrinkage estimation of a spherically symmetric distribution for balanced loss functions," Journal of Multivariate Analysis, Elsevier, vol. 186(C).
    9. Rashad M. EL-Sagheer, 2018. "Estimation of parameters of Weibull–Gamma distribution based on progressively censored data," Statistical Papers, Springer, vol. 59(2), pages 725-757, June.
    10. Xuehua Hu & Wenhao Gui, 2018. "Bayesian and Non-Bayesian Inference for the Generalized Pareto Distribution Based on Progressive Type II Censored Sample," Mathematics, MDPI, vol. 6(12), pages 1-26, December.

    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. Gómez-Déniz, E., 2008. "A generalization of the credibility theory obtained by using the weighted balanced loss function," Insurance: Mathematics and Economics, Elsevier, vol. 42(2), pages 850-854, April.
    2. Cao, Ming-Xiang & He, Dao-Jiang, 2017. "Admissibility of linear estimators of the common mean parameter in general linear models under a balanced loss function," Journal of Multivariate Analysis, Elsevier, vol. 153(C), pages 246-254.
    3. Jafar Ahmadi & Mohammad Jafari Jozani & Éric Marchand & Ahmad Parsian, 2009. "Prediction of k-records from a general class of distributions under balanced type loss functions," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 70(1), pages 19-33, June.
    4. A. Asgharzadeh & N. Sanjari Farsipour, 2008. "Estimation of the exponential mean time to failure under a weighted balanced loss function," Statistical Papers, Springer, vol. 49(1), pages 121-131, March.
    5. Gómez Déniz, E. & Pérez Sánchez, J.M., 2001. "Buenos y malos riesgos en seguros: el punto de vista bayesiano basado en distribuciones bimodales," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 18, pages 175-187, Agosto.
    6. Agata Boratyńska, 2021. "Robust Bayesian insurance premium in a collective risk model with distorted priors under the generalised Bregman loss," Statistics in Transition New Series, Polish Statistical Association, vol. 22(3), pages 123-140, September.
    7. Pérez-Hornero, Patricia & Arias-Nicolás, José Pablo & Pulgarín, Antonio A. & Pulgarín, Antonio, 2013. "An annual JCR impact factor calculation based on Bayesian credibility formulas," Journal of Informetrics, Elsevier, vol. 7(1), pages 1-9.
    8. Emilio Gomez-Deniz & Enrique Calderin-Ojeda, 2010. "A study of Bayesian local robustness with applications in actuarial statistics," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(9), pages 1537-1546.
    9. Kiapour, A. & Nematollahi, N., 2011. "Robust Bayesian prediction and estimation under a squared log error loss function," Statistics & Probability Letters, Elsevier, vol. 81(11), pages 1717-1724, November.
    10. Ali Karimnezhad & Ahmad Parsian, 2018. "Most stable sample size determination in clinical trials," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 27(3), pages 437-454, August.
    11. Gómez Déniz, E. & Pérez Sánchez, J. M., 2001. "Fijación de primas de seguros bajo técnicas de robustez bayesiana," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 19, pages 5-20, Diciembre.
    12. van Akkeren, Marco & Judge, George & Mittelhammer, Ron, 2002. "Generalized moment based estimation and inference," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 127-148, March.
    13. Cao, Mingxiang, 2014. "Admissibility of linear estimators for the stochastic regression coefficient in a general Gauss–Markoff model under a balanced loss function," Journal of Multivariate Analysis, Elsevier, vol. 124(C), pages 25-30.
    14. Gómez Déniz, E. & Hernández Bastida, A. & Vázquez Polo, F.J., 1998. "Un Análisis de Sensibilidad del Proceso de Tarificación en los Seguros Generales," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 9, pages 19-34, Junio.
    15. Sánchez-Sánchez, M. & Sordo, M.A. & Suárez-Llorens, A. & Gómez-Déniz, E., 2019. "Deriving Robust Bayesian Premiums Under Bands Of Prior Distributions With Applications," ASTIN Bulletin, Cambridge University Press, vol. 49(1), pages 147-168, January.
    16. Boratyńska Agata, 2021. "Robust Bayesian insurance premium in a collective risk model with distorted priors under the generalised Bregman loss," Statistics in Transition New Series, Polish Statistical Association, vol. 22(3), pages 123-140, September.
    17. .Fernández Huerga, E., 2004. "Causas de la utilización del empleo temporal y la subcontratación: Análisis empírico de las industrias extractivas en León," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 22, pages 371(30á)-37, Agosto.
    18. Gomez-Deniz, E. & Perez-Sanchez, J.M. & Vazquez-Polo, F.J., 2006. "On the use of posterior regret [Gamma]-minimax actions to obtain credibility premiums," Insurance: Mathematics and Economics, Elsevier, vol. 39(1), pages 115-121, August.
    19. Hobbad, Lahoucine & Marchand, Éric & Ouassou, Idir, 2021. "On shrinkage estimation of a spherically symmetric distribution for balanced loss functions," Journal of Multivariate Analysis, Elsevier, vol. 186(C).
    20. Chaturvedi, Anoop & Shalabh, 2004. "Risk and Pitman closeness properties of feasible generalized double k-class estimators in linear regression models with non-spherical disturbances under balanced loss function," Journal of Multivariate Analysis, Elsevier, vol. 90(2), pages 229-256, August.

    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:53:y:2012:i:1:p:51-60. 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.