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Smooth Design-Adapted Wavelets for Nonparametric Stochastic Regression

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  • V. Delouille
  • J. Simoens
  • R. von Sachs

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  • V. Delouille & J. Simoens & R. von Sachs, 2004. "Smooth Design-Adapted Wavelets for Nonparametric Stochastic Regression," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 643-658, January.
    • Handle: RePEc:bes:jnlasa:v:99:y:2004:p:643-658
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    Cited by:

    1. Nir Billfeld & Moshe Kim, 2019. "Semiparametric Wavelet-based JPEG IV Estimator for endogenously truncated data," Papers 1908.02166, arXiv.org.
    2. Véronique Delouille & Rainer Sachs, 2005. "Estimation of nonlinear autoregressive models using design-adapted wavelets," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 57(2), pages 235-253, June.
    3. Lihong Wang & Haiyan Cai, 2010. "Wavelet change‐point estimation for long memory non‐parametric random design models," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(2), pages 86-97, March.
    4. Timmermans, Catherine & von Sachs, Rainer, 2013. "BAGIDIS: Statistically investigating curves with sharp local patterns using a new functional measure of dissimilarity," LIDAM Discussion Papers ISBA 2013031, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    5. Maarten Jansen & Guy P. Nason & B. W. Silverman, 2009. "Multiscale methods for data on graphs and irregular multidimensional situations," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(1), pages 97-125, January.

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