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Wavelet Threshold Estimators for Data with Correlated Noise

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Cited by:

  1. Morten Ørregaard Nielsen & Per Houmann Frederiksen, 2005. "Finite Sample Comparison of Parametric, Semiparametric, and Wavelet Estimators of Fractional Integration," Econometric Reviews, Taylor & Francis Journals, vol. 24(4), pages 405-443.
  2. Fryzlewicz, Piotr, 2007. "Bivariate hard thresholding in wavelet function estimation," LSE Research Online Documents on Economics 25219, London School of Economics and Political Science, LSE Library.
  3. Serban, Nicoleta, 2010. "Noise reduction for enhanced component identification in multi-dimensional biomolecular NMR studies," Computational Statistics & Data Analysis, Elsevier, vol. 54(4), pages 1051-1065, April.
  4. Fryzlewicz, Piotr, 2008. "Data-driven wavelet-Fisz methodology for nonparametric function estimation," LSE Research Online Documents on Economics 25165, London School of Economics and Political Science, LSE Library.
  5. Catalina Lucia COCIANU & Alexandru Daniel STAN, 2016. "A Novel Noise Removal Method Using Neural Networks," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 20(3), pages 66-75.
  6. Cai, Zongwu & Ren, Yu & Yang, Bingduo, 2015. "A semiparametric conditional capital asset pricing model," Journal of Banking & Finance, Elsevier, vol. 61(C), pages 117-126.
  7. Marcelo M. Taddeo & Pedro A. Morettin, 2023. "Bayesian P-Splines Applied to Semiparametric Models with Errors Following a Scale Mixture of Normals," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(2), pages 1331-1355, August.
  8. Ramsey, J.B., 2002. "Wavelets in Economics and Finance: Past and Future," Working Papers 02-02, C.V. Starr Center for Applied Economics, New York University.
  9. Madison Giacofci & Sophie Lambert-Lacroix & Franck Picard, 2018. "Minimax wavelet estimation for multisample heteroscedastic nonparametric regression," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 30(1), pages 238-261, January.
  10. Wishart, Justin Rory, 2011. "Minimax lower bound for kink location estimators in a nonparametric regression model with long-range dependence," Statistics & Probability Letters, Elsevier, vol. 81(12), pages 1871-1875.
  11. Fryzlewicz, Piotr & Nason, Guy P., 2004. "Smoothing the wavelet periodogram using the Haar-Fisz transform," LSE Research Online Documents on Economics 25231, London School of Economics and Political Science, LSE Library.
  12. Antoniadis, Anestis & Sapatinas, Theofanis, 2003. "Wavelet methods for continuous-time prediction using Hilbert-valued autoregressive processes," Journal of Multivariate Analysis, Elsevier, vol. 87(1), pages 133-158, October.
  13. Lee, Kichun & Vidakovic, Brani, 2012. "Semi-supervised wavelet shrinkage," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1681-1691.
  14. Tanujit Dey & Kun Ho Kim & Chae Young Lim, 2018. "Bayesian time series regression with nonparametric modeling of autocorrelation," Computational Statistics, Springer, vol. 33(4), pages 1715-1731, December.
  15. Zhang, Ting, 2015. "Semiparametric model building for regression models with time-varying parameters," Journal of Econometrics, Elsevier, vol. 187(1), pages 189-200.
  16. Salcedo, Gladys E. & Porto, Rogério F. & Morettin, Pedro A., 2012. "Comparing non-stationary and irregularly spaced time series," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 3921-3934.
  17. Luan, Yihui & Xie, Zhongjie, 2001. "The wavelet identification for jump points of derivative in regression model," Statistics & Probability Letters, Elsevier, vol. 53(2), pages 167-180, June.
  18. G. E. Salcedo & R. F. Porto & S. Y. Roa & F. R. Momo, 2012. "A wavelet-based time-varying autoregressive model for non-stationary and irregular time series," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(11), pages 2313-2325, June.
  19. Kraicová Lucie & Baruník Jozef, 2017. "Estimation of long memory in volatility using wavelets," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(3), pages 1-22, June.
  20. Christophe Chesneau & Fabien Navarro, 2017. "On the pointwise mean squared error of a multidimensional term-by-term thresholding wavelet estimator," Working Papers 2017-68, Center for Research in Economics and Statistics.
  21. repec:jss:jstsof:12:i08 is not listed on IDEAS
  22. Tse, Y.K. & Anh, V.V. & Tieng, Q., 2002. "Maximum likelihood estimation of the fractional differencing parameter in an ARFIMA model using wavelets," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 59(1), pages 153-161.
  23. Beran, Jan & Shumeyko, Yevgen, 2012. "Bootstrap testing for discontinuities under long-range dependence," Journal of Multivariate Analysis, Elsevier, vol. 105(1), pages 322-347.
  24. Porto, Rogério F. & Morettin, Pedro A. & Aubin, Elisete C.Q., 2008. "Wavelet regression with correlated errors on a piecewise Hölder class," Statistics & Probability Letters, Elsevier, vol. 78(16), pages 2739-2743, November.
  25. Iolanda Lo Cascio, 2007. "Wavelet Analysis and Denoising: New Tools for Economists," Working Papers 600, Queen Mary University of London, School of Economics and Finance.
  26. Capobianco Enrico & Marras Elisabetta & Travaglione Antonella, 2011. "Multiscale Characterization of Signaling Network Dynamics through Features," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 10(1), pages 1-32, November.
  27. Sam Efromovich & Jiayi Wu, 2018. "Wavelet Analysis of Big Data Contaminated by Large Noise in an fMRI Study of Neuroplasticity," Methodology and Computing in Applied Probability, Springer, vol. 20(4), pages 1381-1402, December.
  28. McGinnity, K. & Varbanov, R. & Chicken, E., 2017. "Cross-validated wavelet block thresholding for non-Gaussian errors," Computational Statistics & Data Analysis, Elsevier, vol. 106(C), pages 127-137.
  29. Iolanda Lo Cascio, 2007. "Wavelet Analysis and Denoising: New Tools for Economists," Working Papers 600, Queen Mary University of London, School of Economics and Finance.
  30. Capobianco, Enrico, 2004. "Effective decorrelation and space dimensionality reduction of multiscaling volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 340(1), pages 340-346.
  31. Beran, Jan & Heiler, Mark A., 2008. "A nonparametric regression cross spectrum for multivariate time series," Journal of Multivariate Analysis, Elsevier, vol. 99(4), pages 684-714, April.
  32. Beran, Jan, 2008. "A nonparametric regression cross spectrum for multivariate time series," CoFE Discussion Papers 08/01, University of Konstanz, Center of Finance and Econometrics (CoFE).
  33. Linyuan Li & Kewei Lu, 2013. "On rate-optimal nonparametric wavelet regression with long memory moving average errors," Statistical Inference for Stochastic Processes, Springer, vol. 16(2), pages 127-145, July.
  34. Taylor, Larry W., 2009. "Using the Haar wavelet transform in the semiparametric specification of time series," Economic Modelling, Elsevier, vol. 26(2), pages 392-403, March.
  35. Oleg Shestakov, 2020. "Wavelet Thresholding Risk Estimate for the Model with Random Samples and Correlated Noise," Mathematics, MDPI, vol. 8(3), pages 1-8, March.
  36. Capobianco, Enrico, 2003. "Independent Multiresolution Component Analysis and Matching Pursuit," Computational Statistics & Data Analysis, Elsevier, vol. 42(3), pages 385-402, March.
  37. Ramsey James B., 2002. "Wavelets in Economics and Finance: Past and Future," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 6(3), pages 1-29, November.
  38. Capobianco, Enrico, 2008. "Kernel methods and flexible inference for complex stochastic dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(16), pages 4077-4098.
  39. Graham Horgan, 1999. "Using wavelets for data smoothing: A simulation study," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(8), pages 923-932.
  40. Zhang, Shuanglin & Wong, Man-Yu & Zheng, Zhongguo, 2002. "Wavelet Threshold Estimation of a Regression Function with Random Design," Journal of Multivariate Analysis, Elsevier, vol. 80(2), pages 256-284, February.
  41. Chang, Xiao-Wen & Qu, Leming, 2004. "Wavelet estimation of partially linear models," Computational Statistics & Data Analysis, Elsevier, vol. 47(1), pages 31-48, August.
  42. Beran, Jan & Heiler, Mark A., 2007. "Estimation of a nonparametric regression spectrum for multivariate time series," CoFE Discussion Papers 07/12, University of Konstanz, Center of Finance and Econometrics (CoFE).
  43. Linyuan Li & Yimin Xiao, 2007. "Mean Integrated Squared Error of Nonlinear Wavelet-based Estimators with Long Memory Data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 59(2), pages 299-324, June.
  44. Alsaidi M. Altaher & Mohd Tahir Ismail, 2012. "Robust Wavelet Estimation to Eliminate Simultaneously the Effects of Boundary Problems, Outliers, and Correlated Noise," International Journal of Mathematics and Mathematical Sciences, Hindawi, vol. 2012, pages 1-18, November.
  45. Xia, Dong, 2019. "Non-asymptotic bounds for percentiles of independent non-identical random variables," Statistics & Probability Letters, Elsevier, vol. 152(C), pages 111-120.
  46. Gérard Kerkyacharian & Dominique Picard & Lucien Birgé & Peter Hall & Oleg Lepski & Enno Mammen & Alexandre Tsybakov & G. Kerkyacharian & D. Picard, 2000. "Thresholding algorithms, maxisets and well-concentrated bases," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 9(2), pages 283-344, December.
  47. Young Truong & Prakash Patil, 2001. "Asymptotics for Wavelet Based Estimates of Piecewise Smooth Regression for Stationary Time Series," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 53(1), pages 159-178, March.
  48. Kovac, Arne & Silverman, Bernard W., 1998. "Extending the scope of wavelet regression methods by coefficient-dependent thresholding," Technical Reports 1998,05, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
  49. Holger Dette & Martin Kroll, 2022. "Asymptotic equivalence for nonparametric regression with dependent errors: Gauss–Markov processes," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(6), pages 1163-1196, December.
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