[1] Aggarwal C C. Data Streams:Models and Algorithms. Heidelberg: Springer Science & Business Media, 2007. [2] Aggarwal C C, Yu P S. A Survey of Synopsis Construction in Data Streams. Heidelberg: Springer Science & Business Media, 2007. [3] Wrench C, Stahl F, Fatta G, et al. Data stream mining of event and complex event streams: A survey of existing and future technologies and applications in big data. In: Enterprise Big Data Engineering, Analytics, and Management. Hershey, PA: IGI Global, 2016. [4] Cao Y, He H, Man H. SOMKE: Kernel density estimation over data streams by sequences of self-organizing maps. IEEE Transactions on Neural Networks Learning Systems, 2012, 23(8): 1254-1268. [5] Min X, Ishibuchi H, Xin G, et al. Dm-KDE: Dynamical kernel density estimation by sequences of KDE estimators with fixed number of components over data streams. Frontiers of Computer Science, 2014, 8(4): 563-580. [6] Fan J, Gijbels I. Local Polynomial Modelling and Its Applications. Boca Raton, FL: CRC Press, 1996. [7] Härdle W. Applied Nonparametric Regression. Cambridge, UK: Cambridge University Press, 1990. [8] Härdle W, Linton O. Nonparametric regression. SFB Discussion Papers, 1995, 3(2): 867-877. [9] Elizabeth S D, Wu J, Wang C, et al. Online updating of statistical inference in the big data setting. Technometrics, 2016, 58(3): 393-403. [10] Han B, Comaniciu D, Zhu Y, et al. Sequential kernel density approximation and its application to real-time visual tracking. IEEE Transactions on Pattern Analysis Machine Intelligence, 2008, 30(7): 1186-1197. [11] Spurek P, Byrski K, Tabor J. Online updating of active function cross-entropy clustering. Pattern Analysis and Applications, 2019, 22(4): 1409-1425. [12] Kong E, Xia Y. On the efficiency of online approach to nonparametric smoothing of big data. Statistica Sinica, 2019, 29(1): 185-201. [13] Deheuvels P. Estimation nonparamétrique de la densité par histogrammes généralisés. Revue de Statistique Appliquée, 1977, 25(3): 5-42. [14] Stone M. Cross-validation and multinomial prediction. Biometrika, 1974, 61(3): 509-515. [15] Cao R, Cuevas A, Manteiga W G. A comparative study of several smoothing methods in density estimation. Computational Statistics Data Analysis, 1994, 17(2): 153-176. [16] Woodroofe M. On choosing a delta-sequence. Annals of Mathematical Statistics, 1970, 41(5): 1665-1671. [17] Scott D W, Tapia R A, Thompson J R. Kernel density estimation revisited. Nonlinear Analysis Theory Methods Applications, 1977, 1(4): 339-372. [18] Cwik J, Koronacki J. A combined adaptive-mixtures/plug-in estimator of multivariate probability densities. Computational Statistics & Data Analysis, 1997, 26(2): 199-218. [19] Vincent P, Bengio Y. Non-local manifold Parzen windows. In: Advances in Neural Information Processing Systems 15. Cambridge, MA: MIT Press, 2003: 849-856. [20] Whaley R E. Understanding the VIX. The Journal of Portfolio Management, 2009, 35(3): 98-105. [21] Jiang G J, Tian Y S. Extracting model-free volatility from option prices: An examination of the VIX index. The Journal of Derivatives, 2007, 14(3): 35-60. |