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Combining Registration and Fitting for Functional Models

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  • Kneip, Alois
  • Ramsay, James O

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  • Kneip, Alois & Ramsay, James O, 2008. "Combining Registration and Fitting for Functional Models," Journal of the American Statistical Association, American Statistical Association, vol. 103(483), pages 1155-1165.
    • Handle: RePEc:bes:jnlasa:v:103:i:483:y:2008:p:1155-1165
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    Citations

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    Cited by:

    1. Christian Genest & Johanna G. Nešlehová, 2014. "A Conversation with James O. Ramsay," International Statistical Review, International Statistical Institute, vol. 82(2), pages 161-183, August.
    2. Weiyi Xie & Sebastian Kurtek & Karthik Bharath & Ying Sun, 2017. "A Geometric Approach to Visualization of Variability in Functional Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(519), pages 979-993, July.
    3. Simone Vantini, 2012. "On the definition of phase and amplitude variability in functional data analysis," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(4), pages 676-696, December.
    4. Jihui Lee & Gen Li & William F. Christensen & Gavin Collins & Matthew Seeley & Anton E. Bowden & David T. Fullwood & Jeff Goldsmith, 2019. "Functional Data Analyses of Gait Data Measured Using In-Shoe Sensors," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 11(2), pages 288-313, July.
    5. Fang Yao & Yichao Wu & Jialin Zou, 2016. "Probability-enhanced effective dimension reduction for classifying sparse functional data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(1), pages 1-22, March.
    6. Dimeglio, Chloé & Gallón, Santiago & Loubes, Jean-Michel & Maza, Elie, 2014. "A robust algorithm for template curve estimation based on manifold embedding," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 373-386.
    7. Tucker, J. Derek & Wu, Wei & Srivastava, Anuj, 2013. "Generative models for functional data using phase and amplitude separation," Computational Statistics & Data Analysis, Elsevier, vol. 61(C), pages 50-66.
    8. Anthony Ebert & Kerrie Mengersen & Fabrizio Ruggeri & Paul Wu, 2021. "Curve Registration of Functional Data for Approximate Bayesian Computation," Stats, MDPI, vol. 4(3), pages 1-14, September.
    9. Hans-Georg Müller & Wenjing Yang, 2010. "Dynamic relations for sparsely sampled Gaussian processes," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 19(1), pages 1-29, May.
    10. Niels Lundtorp Olsen & Bo Markussen & Lars Lau Raket, 2018. "Simultaneous inference for misaligned multivariate functional data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(5), pages 1147-1176, November.
    11. Irene Albarrán-Lozano & Pablo J. Alonso-González & Ana Arribas-Gil, 2017. "Dependence evolution in the Spanish disabled population: a functional data analysis approach," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(2), pages 657-677, February.
    12. Arribas-Gil, Ana & Müller, Hans-Georg, 2014. "Pairwise dynamic time warping for event data," Computational Statistics & Data Analysis, Elsevier, vol. 69(C), pages 255-268.
    13. Fang Yao & Yichao Wu & Jialin Zou, 2016. "Probability-enhanced effective dimension reduction for classifying sparse functional data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(1), pages 1-22, March.
    14. Cody Carroll & Hans‐Georg Müller, 2023. "Latent deformation models for multivariate functional data and time‐warping separability," Biometrics, The International Biometric Society, vol. 79(4), pages 3345-3358, December.
    15. Jason Cleveland & Wei Wu & Anuj Srivastava, 2016. "Norm-preserving constraint in the Fisher--Rao registration and its application in signal estimation," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 28(2), pages 338-359, June.
    16. Cleveland, Jason & Zhao, Weilong & Wu, Wei, 2018. "Robust template estimation for functional data with phase variability using band depth," Computational Statistics & Data Analysis, Elsevier, vol. 125(C), pages 10-26.
    17. Daniel Gervini & Patrick A. Carter, 2014. "Warped functional analysis of variance," Biometrics, The International Biometric Society, vol. 70(3), pages 526-535, September.
    18. Juhyun Park & Jeongyoun Ahn, 2017. "Clustering multivariate functional data with phase variation," Biometrics, The International Biometric Society, vol. 73(1), pages 324-333, March.
    19. Derek Tucker, J. & Shand, Lyndsay & Chowdhary, Kenny, 2021. "Multimodal Bayesian registration of noisy functions using Hamiltonian Monte Carlo," Computational Statistics & Data Analysis, Elsevier, vol. 163(C).
    20. Julia Wrobel & Vadim Zipunnikov & Jennifer Schrack & Jeff Goldsmith, 2019. "Registration for exponential family functional data," Biometrics, The International Biometric Society, vol. 75(1), pages 48-57, March.
    21. Gerda Claeskens & Bernard W. Silverman & Leen Slaets, 2010. "A multiresolution approach to time warping achieved by a Bayesian prior–posterior transfer fitting strategy," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(5), pages 673-694, November.
    22. Wagner, Heiko & Kneip, Alois, 2019. "Nonparametric registration to low-dimensional function spaces," Computational Statistics & Data Analysis, Elsevier, vol. 138(C), pages 49-63.

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