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Wavelet estimation of the dimensionality of curve time series. (2020). Fonseca, Rodney V ; Pinheiro, Aluisio.
In: Annals of the Institute of Statistical Mathematics.
RePEc:spr:aistmt:v:72:y:2020:i:5:d:10.1007_s10463-019-00724-4.

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  1. Abadir, K. M., Caggiano, G., Talmain, G. (2013). Nelson–Plosser revisited: The ACF approach. Journal of Econometrics, 175(1), 22–34.

  2. Abraham, B. (1982). Temporal aggregation and time series. International Statistical Review/Revue Internationale de Statistique, 50(3), 285–291.
    Paper not yet in RePEc: Add citation now
  3. Amato, U., Antoniadis, A., De Feis, I., Goude, Y. (2017). Estimation and group variable selection for additive partial linear models with wavelets and splines. South African Statistical Journal, 51(2), 235–272.
    Paper not yet in RePEc: Add citation now
  4. Amighini, A., Bongiorno, E. G., Goia, A. (2014). A clustering method for economic aggregates by using concentration curves. Contributions in infinite-dimensional statistics and related topics, pp. 25–30. Bologna: Esculapio.
    Paper not yet in RePEc: Add citation now
  5. Aneiros, G., Vieu, P. (2016). Comments on: Probability enhanced effective dimension reduction for classifying sparse functional data. TEST, 25(1), 27–32.

  6. Aue, A., Horváth, L., Pellatt, D. F. (2017). Functional generalized autoregressive conditional heteroskedasticity. Journal of Time Series Analysis, 38(1), 3–21.

  7. Bathia, N., Yao, Q., Ziegelmann, F. (2010). Identifying the finite dimensionality of curve time series. The Annals of Statistics, 38(6), 3352–3386.
    Paper not yet in RePEc: Add citation now
  8. Belloni, A., Chernozhukov, V., Fernández-Val, I., Hansen, C. (2017). Program evaluation and causal inference with high-dimensional data. Econometrica, 85(1), 233–298.

  9. Berry, S. T., Haile, P. A. (2014). Identification in differentiated products markets using market level data. Econometrica, 82(5), 1749–1797.

  10. Bosq, D. (2000). Linear processes in function spaces: Theory and applications. New York: Springer.
    Paper not yet in RePEc: Add citation now
  11. Breunig, C., Johannes, J. (2016). Adaptive estimation of functionals in nonparametric instrumental regression. Econometric Theory, 32(3), 612–654.

  12. Canale, A., Ruggiero, M. (2016). Bayesian nonparametric forecasting of monotonic functional time series. Electronic Journal of Statistics, 10(2), 3265–3286.
    Paper not yet in RePEc: Add citation now
  13. Chacón, J. E., Rodríguez-Casal, A. (2005). On the l1-consistency of wavelet density estimates. Canadian Journal of Statistics, 33(4), 489–496.
    Paper not yet in RePEc: Add citation now
  14. Cholaquidis, A., Fraiman, R., Kalemkerian, J., Llop, P. (2014). An optimal aggregation type classifier. In Contributions in infinite-dimensional statistics and related topics (pp 85–90). Bologna: Esculapio.
    Paper not yet in RePEc: Add citation now
  15. Comte, F., Mabon, G., Samson, A. (2017). Spline regression for hazard rate estimation when data are censored and measured with error. Statistica Neerlandica, 71(2), 115–140.

  16. Devijver, E. (2017). Model-based regression clustering for high-dimensional data: Application to functional data. Advances in Data Analysis and Classification, 11(2), 243–279.

  17. Dias, R., Garcia, N. L., Ludwig, G., Saraiva, M. A. (2015). Aggregated functional data model for near-infrared spectroscopy calibration and prediction. Journal of Applied Statistics, 42(1), 127–143.

  18. Dias, R., Garcia, N. L., Schmidt, A. M. (2013). A hierarchical model for aggregated functional data. Technometrics, 55(3), 321–334.
    Paper not yet in RePEc: Add citation now
  19. Donoho, D. L., Johnstone, J. M. (1994). Ideal spatial adaptation by wavelet shrinkage. Biometrika, 81(3), 425–455.
    Paper not yet in RePEc: Add citation now
  20. Fan, Y., James, G. M., Radchenko, P. (2015). Functional additive regression. The Annals of Statistics, 43(5), 2296–2325.
    Paper not yet in RePEc: Add citation now
  21. Härdle, W., Kerkyacharian, G., Picard, D., Tsybakov, A. (1998). Wavelets, approximation, and statistical applications. New York: Springer.
    Paper not yet in RePEc: Add citation now
  22. Hall, P., Vial, C. (2006). Assessing the finite dimensionality of functional data. Journal of the Royal Statistical Society, Series B, 68(4), 689–705.

  23. Hooker, G., Roberts, S. (2016). Maximal autocorrelation functions in functional data analysis. Statistics and Computing, 26(5), 945–950.
    Paper not yet in RePEc: Add citation now
  24. Horta, E., Ziegelmann, F. (2016). Identifying the spectral representation of Hilbertian time series. Statistics & Probability Letters, 118, 45–49.

  25. Horta, E., Ziegelmann, F. (2018). Dynamics of financial returns densities: A functional approach applied to the Bovespa intraday index. International Journal of Forecasting, 34(1), 75–88.

  26. Horváth, L., Kokoszka, P., Rice, G. (2014). Testing stationarity of functional time series. Journal of Econometrics, 179(1), 66–82.

  27. Hyndman, R. J., Ullah, M. S. (2007). Robust forecasting of mortality and fertility rates: A functional data approach. Computational Statistics & Data Analysis, 51(10), 4942–4956.

  28. Imaizumi, M., Kato, K. (2018). PCA-based estimation for functional linear regression with functional responses. Journal of Multivariate Analysis, 163, 15–36.

  29. Ivanescu, A. E. (2017). Adaptive inference for the bivariate mean function in functional data. Advances in Data Science and Adaptive Analysis, 9(3), 1750005.
    Paper not yet in RePEc: Add citation now
  30. Johnstone, I. M., Lu, A. Y. (2009). On consistency and sparsity for principal components analysis in high dimensions. Journal of the American Statistical Association, 104(486), 682–693.

  31. Lakraj, G. P., Ruymgaart, F. (2017). Some asymptotic theory for Silverman’s smoothed functional principal components in an abstract Hilbert space. Journal of Multivariate Analysis, 155, 122–132.

  32. Li, B., Song, J. (2017). Nonlinear sufficient dimension reduction for functional data. The Annals of Statistics, 45(3), 1059–1095.
    Paper not yet in RePEc: Add citation now
  33. Li, G., Shen, H., Huang, J. Z. (2016). Supervised sparse and functional principal component analysis. Journal of Computational and Graphical Statistics, 25(3), 859–878.
    Paper not yet in RePEc: Add citation now
  34. Lorenz, D. A., Resmerita, E. (2017). Flexible sparse regularization. Inverse Problems, 33(1), 014002.
    Paper not yet in RePEc: Add citation now
  35. Mallat, S. G. (1989). A theory for multiresolution signal decomposition: The wavelet representation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 11(7), 674–693.
    Paper not yet in RePEc: Add citation now
  36. Mallat, S. G. (1998). A wavelet tour of signal processing. San Diego: Academic Press.
    Paper not yet in RePEc: Add citation now
  37. Masry, E. (1994). Probability density estimation from dependent observations using wavelets orthonormal bases. Statistics & Probability Letters, 21(3), 181–194.

  38. Masry, E. (1997). Multivariate probability density estimation by wavelet methods: Strong consistency and rates for stationary time series. Stochastic Processes and Their Applications, 67(2), 177–193.

  39. Mirafzal, S. M. (2018). More odd graph theory from another point of view. Discrete Mathematics, 341(1), 217–220.
    Paper not yet in RePEc: Add citation now
  40. Morettin, P. A., Pinheiro, A., Vidakovic, B. (2017). Wavelets in functional data analysis. Cham: Springer.
    Paper not yet in RePEc: Add citation now
  41. Mousavi, S. N., Sørensen, H. (2018). Functional logistic regression: A comparison of three methods. Journal of Statistical Computation and Simulation, 88(2), 250–268.
    Paper not yet in RePEc: Add citation now
  42. Pakoš, M. (2011). Estimating intertemporal and intratemporal substitutions when both income and substitution effects are present: The role of durable goods. Journal of Business & Economic Statistics, 29(3), 439–454.

  43. Percival, D., Sardy, S., Davison, A. (2000). Nonlinear and nonstationary signal processing, chapter Wavestrapping time series: Adaptive wavelet-based bootstrapping, pp. 442–471. Cambridge: Cambridge University Press.
    Paper not yet in RePEc: Add citation now
  44. Pinheiro, A., Vidakovic, B. (1997). Estimating the square root of a density via compactly supported wavelets. Computational Statistics & Data Analysis, 25(4), 399–415.

  45. Qu, L., Song, X., Sun, L. (2018). Identification of local sparsity and variable selection for varying coefficient additive hazards models. Computational Statistics & Data Analysis, 125, 119–135.

  46. Røislien, J., Winje, B. (2013). Feature extraction across individual time series observations with spikes using wavelet principal component analysis. Statistics in Medicine, 32(21), 3660–3669.
    Paper not yet in RePEc: Add citation now
  47. Ramsay, J. O., Silverman, B. W. (2005). Functional data analysis2nd ed. New York: Springer.
    Paper not yet in RePEc: Add citation now
  48. Salvatore, S., Bramness, J. G., Røislien, J. (2016). Exploring functional data analysis and wavelet principal component analysis on ecstasy (MDMA) wastewater data. BMC Medical Research Methodology, 16, 81.
    Paper not yet in RePEc: Add citation now
  49. Schillings, C., Schwab, C. (2016). Scaling limits in computational Bayesian inversion. ESAIM: Mathematical Modelling and Numerical Analysis, 50(6), 1825–1856.
    Paper not yet in RePEc: Add citation now
  50. Shang, H. L. (2016). Mortality and life expectancy forecasting for a group of populations in developed countries: A multilevel functional data method. The Annals of Applied Statistics, 10(3), 1639–1672.
    Paper not yet in RePEc: Add citation now
  51. Sienkiewicz, E., Song, D., Breidt, F. J., Wang, H. (2017). Sparse functional dynamical models—A big data approach. Journal of Computational and Graphical Statistics, 26(2), 319–329.
    Paper not yet in RePEc: Add citation now
  52. Suarez, A. J., Ghosal, S. (2017). Bayesian estimation of principal components for functional data. Bayesian Analysis, 12(2), 311–333.
    Paper not yet in RePEc: Add citation now
  53. Vidakovic, B. (1999). Statistical modeling by wavelets. New York: Wiley.
    Paper not yet in RePEc: Add citation now
  54. Voronin, S., Daubechies, I. (2017). An iteratively reweighted least squares algorithm for sparse regularization. In Functional analysis, harmonic analysis, and image processing: A collection of papers in honor of Björn Jawerth, volume 693 of Contemporary Mathematics (pp. 391–411). Providence: American Mathematical Society.
    Paper not yet in RePEc: Add citation now
  55. Wei, W. (2006). Time series analysis: Univariate and multivariate methods2nd ed. Boston: Pearson.
    Paper not yet in RePEc: Add citation now
  56. Yan, H., Paynabar, K., Shi, J. (2018). Real-time monitoring of high-dimensional functional data streams via spatio-temporal smooth sparse decomposition. Technometrics, 60(2), 181–197.
    Paper not yet in RePEc: Add citation now
  57. Yang, J., Stahl, D., Shen, Z. (2017). An analysis of wavelet frame based scattered data reconstruction. Applied and Computational Harmonic Analysis, 42(3), 480–507.
    Paper not yet in RePEc: Add citation now
  58. Yao, F., Wu, Y., Zou, J. (2016). Probability-enhanced effective dimension reduction for classifying sparse functional data. TEST, 25(1), 1–22.

  59. Zhang, J., Blum, R. S., Kaplan, L. M., Lu, X. (2017). Functional forms of optimum spoofing attacks for vector parameter estimation in quantized sensor networks. IEEE Transactions on Signal Processing, 65(3), 705–720.
    Paper not yet in RePEc: Add citation now
  60. Zhang, X., Wang, C., Wu, Y. (2018). Functional envelope for model-free sufficient dimension reduction. Journal of Multivariate Analysis, 163, 37–50.

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