IDEAS home Printed from https://ideas.repec.org/a/spr/metrik/v75y2012i1p5-22.html
   My bibliography  Save this article

Fuzzy density estimation

Author

Listed:
  • Mohsen Arefi
  • Reinhard Viertl
  • S. Taheri

Abstract

No abstract is available for this item.

Suggested Citation

  • Mohsen Arefi & Reinhard Viertl & S. Taheri, 2012. "Fuzzy density estimation," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 75(1), pages 5-22, January.
  • Handle: RePEc:spr:metrik:v:75:y:2012:i:1:p:5-22
    DOI: 10.1007/s00184-010-0311-y
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s00184-010-0311-y
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s00184-010-0311-y?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. Alberts, T. & Karunamuni, R. J., 2003. "A semiparametric method of boundary correction for kernel density estimation," Statistics & Probability Letters, Elsevier, vol. 61(3), pages 287-298, February.
    2. Wu, Tiee-Jian & Chen, Ching-Fu & Chen, Huang-Yu, 2007. "A variable bandwidth selector in multivariate kernel density estimation," Statistics & Probability Letters, Elsevier, vol. 77(4), pages 462-467, February.
    3. Viertl, Reinhard, 2006. "Univariate statistical analysis with fuzzy data," Computational Statistics & Data Analysis, Elsevier, vol. 51(1), pages 133-147, November.
    4. Ker, Alan P. & Ergün, A.T., 2005. "Empirical Bayes nonparametric kernel density estimation," Statistics & Probability Letters, Elsevier, vol. 75(4), pages 315-324, December.
    5. Loquin, Kevin & Strauss, Olivier, 2008. "Histogram density estimators based upon a fuzzy partition," Statistics & Probability Letters, Elsevier, vol. 78(13), pages 1863-1868, September.
    6. Campos, V. S. M. & Dorea, C. C. Y., 2001. "Kernel density estimation: the general case," Statistics & Probability Letters, Elsevier, vol. 55(2), pages 173-180, November.
    7. Lee, Y. K. & Choi, H. & Park, B. U. & Yu, K. S., 2004. "Local likelihood density estimation on random fields," Statistics & Probability Letters, Elsevier, vol. 68(4), pages 347-357, July.
    8. Hazelton, Martin L., 2000. "Marginal density estimation from incomplete bivariate data," Statistics & Probability Letters, Elsevier, vol. 47(1), pages 75-84, March.
    9. Konstantinos Fokianos, 2004. "Merging information for semiparametric density estimation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(4), pages 941-958, November.
    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. Catalina Bolance & Montserrat Guillen & David Pitt, 2014. "Non-parametric Models for Univariate Claim Severity Distributions - an approach using R," Working Papers 2014-01, Universitat de Barcelona, UB Riskcenter.
    2. Muhammad Aslam, 2022. "Neutrosophic F-Test for Two Counts of Data from the Poisson Distribution with Application in Climatology," Stats, MDPI, vol. 5(3), pages 1-11, August.
    3. Bolancé, Catalina & Guillén, Montserrat & Nielsen, Jens Perch, 2008. "Inverse beta transformation in kernel density estimation," Statistics & Probability Letters, Elsevier, vol. 78(13), pages 1757-1764, September.
    4. David Pitt & Montserrat Guillen & Catalina Bolancé, 2011. "Estimation of Parametric and Nonparametric Models for Univariate Claim Severity Distributions - an approach using R," Working Papers XREAP2011-06, Xarxa de Referència en Economia Aplicada (XREAP), revised Jun 2011.
    5. Mojirsheibani, Majid & Montazeri, Zahra, 2007. "On nonparametric classification with missing covariates," Journal of Multivariate Analysis, Elsevier, vol. 98(5), pages 1051-1071, May.
    6. OrI Davidov & Konstantinos Fokianos & George Iliopoulos, 2014. "Semiparametric Inference for the Two-way Layout Under Order Restrictions," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(3), pages 622-638, September.
    7. Madan Mohan Rout & Josodhir Das & Kamal, 2018. "Probabilistic seismic hazard for Himalayan region using kernel estimation method (zone-free method)," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 93(2), pages 967-985, September.
    8. Xuze Zhang & Saumyadipta Pyne & Benjamin Kedem, 2020. "Estimation of residential radon concentration in Pennsylvania counties by data fusion," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 36(6), pages 1094-1110, November.
    9. Majid Mojirsheibani & Zahra Montazeri, 2007. "Statistical classification with missing covariates," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 69(5), pages 839-857, November.
    10. Viviane Campos & Chang Dorea, 2005. "Kernel estimation for stationary density of Markov chains with general state space," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 57(3), pages 443-453, September.
    11. Tang Qingguo & Chen Wenyu, 2022. "Estimation for partially linear additive regression with spatial data," Statistical Papers, Springer, vol. 63(6), pages 2041-2063, December.
    12. Zhengyan Lin & Degui Li & Jiti Gao, 2009. "Local Linear M‐estimation in non‐parametric spatial regression," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(3), pages 286-314, May.
    13. Ori Davidov & Konstantinos Fokianos & George Iliopoulos, 2010. "Order-Restricted Semiparametric Inference for the Power Bias Model," Biometrics, The International Biometric Society, vol. 66(2), pages 549-557, June.
    14. Abbas Parchami & S. Taheri & Mashaallah Mashinchi, 2012. "Testing fuzzy hypotheses based on vague observations: a p-value approach," Statistical Papers, Springer, vol. 53(2), pages 469-484, May.
    15. Pierpaolo D’Urso & María Ángeles Gil, 2017. "Fuzzy data analysis and classification," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 11(4), pages 645-657, December.
    16. Subhadip Bandyopadhyay & Arup Bose & Debasis Sengupta, 2010. "Nonparametric estimation of multivariate density with direct and auxiliary data and application," Indian Journal of Pure and Applied Mathematics, Springer, vol. 41(1), pages 251-274, February.
    17. Kangning Wang, 2018. "Variable selection for spatial semivarying coefficient models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 70(2), pages 323-351, April.
    18. Xijian Hu & Yaori Lu & Huiguo Zhang & Haijun Jiang & Qingdong Shi, 2021. "Selection of the Bandwidth Matrix in Spatial Varying Coefficient Models to Detect Anisotropic Regression Relationships," Mathematics, MDPI, vol. 9(18), pages 1-14, September.
    19. David Pitt & Montserrat Guillén, 2010. "An introduction to parametric and non-parametric models for bivariate positive insurance claim severity distributions," Working Papers XREAP2010-03, Xarxa de Referència en Economia Aplicada (XREAP), revised Mar 2010.
    20. Yi Jin & Yulin He & Defa Huang, 2021. "An Improved Variable Kernel Density Estimator Based on L 2 Regularization," Mathematics, MDPI, vol. 9(16), pages 1-12, 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:metrik:v:75:y:2012:i:1:p:5-22. 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: 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.