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Functional mixed effects wavelet estimation for spectra of replicated time series

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  • Chau, Van Vinh
  • von Sachs, Rainer

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  • Chau, Van Vinh & von Sachs, Rainer, 2016. "Functional mixed effects wavelet estimation for spectra of replicated time series," LIDAM Discussion Papers ISBA 2016013, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    • Handle: RePEc:aiz:louvad:2016013
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    References listed on IDEAS

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    1. M. Giacofci & S. Lambert-Lacroix & G. Marot & F. Picard, 2013. "Wavelet-Based Clustering for Mixed-Effects Functional Models in High Dimension," Biometrics, The International Biometric Society, vol. 69(1), pages 31-40, March.
    2. Michael H. Neumann, 1996. "Spectral Density Estimation Via Nonlinear Wavelet Methods For Stationary Non‐Gaussian Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 17(6), pages 601-633, November.
    3. John A. D. Aston & Jeng‐Min Chiou & Jonathan P. Evans, 2010. "Linguistic pitch analysis using functional principal component mixed effect models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 59(2), pages 297-317, March.
    4. Hernandez-Flores, C. N. & Artiles-Romero, J. & Saavedra-Santana, P., 1999. "Estimation of the population spectrum with replicated time series," Computational Statistics & Data Analysis, Elsevier, vol. 30(3), pages 271-280, May.
    5. Jeffrey S. Morris & Philip J. Brown & Richard C. Herrick & Keith A. Baggerly & Kevin R. Coombes, 2008. "Bayesian Analysis of Mass Spectrometry Proteomic Data Using Wavelet-Based Functional Mixed Models," Biometrics, The International Biometric Society, vol. 64(2), pages 479-489, June.
    6. Wensheng Guo, 2002. "Functional Mixed Effects Models," Biometrics, The International Biometric Society, vol. 58(1), pages 121-128, March.
    7. Ombao, Hernando & von Sachs, Rainer & Guo, Wensheng, 2005. "SLEX Analysis of Multivariate Nonstationary Time Series," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 519-531, June.
    8. Josue G. Martinez & Kirsten M. Bohn & Raymond J. Carroll & Jeffrey S. Morris, 2013. "A Study of Mexican Free-Tailed Bat Chirp Syllables: Bayesian Functional Mixed Models for Nonstationary Acoustic Time Series," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(502), pages 514-526, June.
    9. Mark Fiecas & Hernando Ombao, 2016. "Modeling the Evolution of Dynamic Brain Processes During an Associative Learning Experiment," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(516), pages 1440-1453, October.
    10. Antoniadis, Anestis & Sapatinas, Theofanis, 2007. "Estimation and inference in functional mixed-effects models," Computational Statistics & Data Analysis, Elsevier, vol. 51(10), pages 4793-4813, June.
    11. Jeffrey S. Morris & Raymond J. Carroll, 2006. "Wavelet‐based functional mixed models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 68(2), pages 179-199, April.
    12. Cristina Gorrostieta & Hernando Ombao & Raquel Prado & Shaun Patel & Emad Eskandar, 2012. "Exploring dependence between brain signals in a monkey during learning," Journal of Time Series Analysis, Wiley Blackwell, vol. 33(5), pages 771-778, September.
    13. Robert T. Krafty & Martica Hall & Wensheng Guo, 2011. "Functional mixed effects spectral analysis," Biometrika, Biometrika Trust, vol. 98(3), pages 583-598.
    14. Hong‐Ye Gao, 1997. "Choice of thresholds for wavelet shrinkage estimate of the spectrum," Journal of Time Series Analysis, Wiley Blackwell, vol. 18(3), pages 231-251, May.
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    Cited by:

    1. Chau, Van Vinh & Ombao, Hernando & von Sachs, Rainer, 2017. "Data depth and rank-based tests for covariance and spectral density matrices," LIDAM Discussion Papers ISBA 2017019, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    2. Chau, Van Vinh & von Sachs, Rainer, 2017. "Positive-Definite Multivariate Spectral Estimation: A Geometric Wavelet Approach," LIDAM Discussion Papers ISBA 2017002, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    3. Krebs, Johannes & Rademacher, Daniel & von Sachs, Rainer, 2022. "Statistical inference for intrinsic wavelet estimators of SPD covariance matrices in a log-Euclidean manifold," LIDAM Discussion Papers ISBA 2022004, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    4. von Sachs, Rainer, 2019. "Spectral Analysis of Multivariate Time Series," LIDAM Discussion Papers ISBA 2019008, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    5. Yakun Wang & Zeda Li & Scott A. Bruce, 2023. "Adaptive Bayesian sum of trees model for covariate‐dependent spectral analysis," Biometrics, The International Biometric Society, vol. 79(3), pages 1826-1839, September.

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