IDEAS home Printed from https://ideas.repec.org/r/eee/csdana/v17y1994i2p153-176.html
   My bibliography  Save this item

A comparative study of several smoothing methods in density estimation

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. C. Sánchez-Sellero & W. González-Manteiga & R. Cao, 1999. "Bandwidth Selection in Density Estimation with Truncated and Censored Data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 51(1), pages 51-70, March.
  2. García-Portugués, Eduardo & Crujeiras, Rosa M. & González-Manteiga, Wenceslao, 2013. "Kernel density estimation for directional–linear data," Journal of Multivariate Analysis, Elsevier, vol. 121(C), pages 152-175.
  3. Jin Zhang, 2015. "Generalized least squares cross-validation in kernel density estimation," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 69(3), pages 315-328, August.
  4. Ichimura, Hidehiko & Todd, Petra E., 2007. "Implementing Nonparametric and Semiparametric Estimators," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 6, chapter 74, Elsevier.
  5. J. M. Vilar & R. Cao & M. C. Ausin & C. Gonzalez-Fragueiro, 2009. "Nonparametric analysis of aggregate loss models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 36(2), pages 149-166.
  6. Wen-Ching Wang, 2018. "Setting up evaluate indicators for slope control engineering based on spatial clustering analysis," 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 921-939, September.
  7. Miśkiewicz, Janusz, 2016. "Improving quality of sample entropy estimation for continuous distribution probability functions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 473-485.
  8. Jonas Rothfuss & Fabio Ferreira & Simon Walther & Maxim Ulrich, 2019. "Conditional Density Estimation with Neural Networks: Best Practices and Benchmarks," Papers 1903.00954, arXiv.org, revised Apr 2019.
  9. Filippone, Maurizio & Sanguinetti, Guido, 2011. "Approximate inference of the bandwidth in multivariate kernel density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 55(12), pages 3104-3122, December.
  10. David Atienza & Pedro Larrañaga & Concha Bielza, 2022. "Hybrid semiparametric Bayesian networks," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(2), pages 299-327, June.
  11. Moreira , Carla & Van Keilegom, Ingrid, 2012. "Bandwidth Selection for Kernel Density Estimation with Doubly Truncated Data," LIDAM Discussion Papers ISBA 2012006, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  12. Heiler, Siegfried & Feng, Yuanhua, 1997. "A bootstrap bandwidth selector for local polynomial fitting," Discussion Papers, Series II 344, University of Konstanz, Collaborative Research Centre (SFB) 178 "Internationalization of the Economy".
  13. Isabel Fuentes-Santos & Wenceslao González-Manteiga & Jorge Mateu, 2016. "Consistent Smooth Bootstrap Kernel Intensity Estimation for Inhomogeneous Spatial Poisson Point Processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(2), pages 416-435, June.
  14. Emili Tortosa-Ausina, 2000. "Inefficient banks or inefficient assets," Working Papers 0005, Departament Empresa, Universitat Autònoma de Barcelona, revised Dec 2000.
  15. Chacón, José E. & Fernández Serrano, Javier, 2024. "Bayesian taut splines for estimating the number of modes," Computational Statistics & Data Analysis, Elsevier, vol. 196(C).
  16. T. Sclocco & M. Marzio, 2001. "A note on kernel density estimation for non-negative random variables," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 10(1), pages 67-79, January.
  17. Cwik, J. & Koronacki, J., 1997. "A combined adaptive-mixtures/plug-in estimator of multivariate probability densities," Computational Statistics & Data Analysis, Elsevier, vol. 26(2), pages 199-218, December.
  18. Bose, Arup & Dutta, Santanu, 2013. "Density estimation using bootstrap bandwidth selector," Statistics & Probability Letters, Elsevier, vol. 83(1), pages 245-256.
  19. J. S. Marron & S. S. Chung, 2001. "Presentation of smoothers: the family approach," Computational Statistics, Springer, vol. 16(1), pages 195-207, March.
  20. Emili Tortosa-Ausina, 2003. "Bank cost efficiency as distribution dynamics: controlling for specialization is important," Investigaciones Economicas, Fundación SEPI, vol. 27(1), pages 71-96, January.
  21. Matthew A. Masten & Alexandre Poirier, 2020. "Inference on breakdown frontiers," Quantitative Economics, Econometric Society, vol. 11(1), pages 41-111, January.
  22. Adriano Z. Zambom & Ronaldo Dias, 2013. "A Review of Kernel Density Estimation with Applications to Econometrics," International Econometric Review (IER), Econometric Research Association, vol. 5(1), pages 20-42, April.
  23. Sohn, Keemin & Kim, Daehyun, 2010. "Zonal centrality measures and the neighborhood effect," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(9), pages 733-743, November.
  24. Duc Devroye & J. Beirlant & R. Cao & R. Fraiman & P. Hall & M. Jones & Gábor Lugosi & E. Mammen & J. Marron & C. Sánchez-Sellero & J. Uña & F. Udina & L. Devroye, 1997. "Universal smoothing factor selection in density estimation: theory and practice," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 6(2), pages 223-320, December.
  25. Klemelä, Jussi, 2000. "Estimation of Densities and Derivatives of Densities with Directional Data," Journal of Multivariate Analysis, Elsevier, vol. 73(1), pages 18-40, April.
  26. Necla Gündüz & Şule Karakoç, 2023. "Optimal Bandwidth Selection Methods with Application to Wind Speed Distribution," Mathematics, MDPI, vol. 11(21), pages 1-21, October.
  27. Gonzalez-Manteiga, W. & Sanchez-Sellero, C. & Wand, M. P., 1996. "Accuracy of binned kernel functional approximations," Computational Statistics & Data Analysis, Elsevier, vol. 22(1), pages 1-16, June.
  28. Delaigle, A. & Gijbels, I., 2004. "Practical bandwidth selection in deconvolution kernel density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 45(2), pages 249-267, March.
  29. Farmen, Mark & Marron, J. S., 1999. "An assessment of finite sample performance of adaptive methods in density estimation," Computational Statistics & Data Analysis, Elsevier, vol. 30(2), pages 143-168, April.
  30. Barbeito, Inés & Cao, Ricardo, 2016. "Smoothed stationary bootstrap bandwidth selection for density estimation with dependent data," Computational Statistics & Data Analysis, Elsevier, vol. 104(C), pages 130-147.
  31. Jinxin Wang & Chi Zhang & Xiuzhen Ma & Zhongwei Wang & Yuandong Xu & Robert Cattley, 2020. "A Multivariate Statistics-Based Approach for Detecting Diesel Engine Faults with Weak Signatures," Energies, MDPI, vol. 13(4), pages 1-14, February.
  32. M. Jácome & I. Gijbels & R. Cao, 2008. "Comparison of presmoothing methods in kernel density estimation under censoring," Computational Statistics, Springer, vol. 23(3), pages 381-406, July.
  33. Moreira, C. & Van Keilegom, I., 2013. "Bandwidth selection for kernel density estimation with doubly truncated data," Computational Statistics & Data Analysis, Elsevier, vol. 61(C), pages 107-123.
  34. Heiler, Siegfried & Feng, Yuanhua, 1995. "A simple root n bandwidth selector for nonparametric regression," Discussion Papers, Series II 286, University of Konstanz, Collaborative Research Centre (SFB) 178 "Internationalization of the Economy".
  35. Wang, Fahui & Antipova, Anzhelika & Porta, Sergio, 2011. "Street centrality and land use intensity in Baton Rouge, Louisiana," Journal of Transport Geography, Elsevier, vol. 19(2), pages 285-293.
  36. Maria Jácome & Ricardo Cao, 2008. "Asymptotic-based bandwidth selection for the presmoothed density estimator with censored data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 20(6), pages 483-506.
  37. Tortosa-Ausina, Emili, 2002. "Exploring efficiency differences over time in the Spanish banking industry," European Journal of Operational Research, Elsevier, vol. 139(3), pages 643-664, June.
  38. Zhenyu Jiang & Nengxiang Ling & Zudi Lu & Dag Tj⊘stheim & Qiang Zhang, 2020. "On bandwidth choice for spatial data density estimation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 82(3), pages 817-840, July.
  39. Nils-Bastian Heidenreich & Anja Schindler & Stefan Sperlich, 2013. "Bandwidth selection for kernel density estimation: a review of fully automatic selectors," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 97(4), pages 403-433, October.
  40. Eibelshäuser, Steffen & Wilhelm, Sascha, 2017. "Markets Take Breaks: Dynamic Price Competition with Opening Hours," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168247, Verein für Socialpolitik / German Economic Association.
  41. Dajun Dai & Fahui Wang, 2011. "Geographic Disparities in Accessibility to Food Stores in Southwest Mississippi," Environment and Planning B, , vol. 38(4), pages 659-677, August.
  42. Jos'e E. Figueroa-L'opez & Cheng Li, 2016. "Optimal Kernel Estimation of Spot Volatility of Stochastic Differential Equations," Papers 1612.04507, arXiv.org.
  43. Horová, Ivana & Koláček, Jan & Vopatová, Kamila, 2013. "Full bandwidth matrix selectors for gradient kernel density estimate," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 364-376.
  44. Hirukawa Masayuki, 2004. "A Two-Stage Plug-In Bandwidth Selection and Its Implementation in Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Working Papers 04005, Concordia University, Department of Economics.
  45. Emili Tortosa Ausina, 1999. "-Convergence In Efficiency Of The Spanish Banking Firms As Distribution Dynamics," Working Papers. Serie EC 1999-14, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
  46. Sergio Porta & Emanuele Strano & Valentino Iacoviello & Roberto Messora & Vito Latora & Alessio Cardillo & Fahui Wang & Salvatore Scellato, 2009. "Street Centrality and Densities of Retail and Services in Bologna, Italy," Environment and Planning B, , vol. 36(3), pages 450-465, June.
  47. del Rio, Alejandro Quintela, 1996. "Comparison of bandwidth selectors in nonparametric regression under dependence," Computational Statistics & Data Analysis, Elsevier, vol. 21(5), pages 563-580, May.
  48. Dutta, Santanu & Goswami, Alok, 2013. "Pointwise and uniform convergence of kernel density estimators using random bandwidths," Statistics & Probability Letters, Elsevier, vol. 83(12), pages 2711-2720.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.