Applied Functional Data Analysis: Methods and Case Studies

By T. Auton. 2004

177 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/89cca1561c853229d64ee11b1dd3cfda46d98a69

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In Statistics and Probability

Citations in the corpus

Valuation of large variable annuity portfolios under nested simulation: A functional data approach (2015, methodology): “Functional data analysis as a branch of statistics focuses on analyzing functional data, which includes curves and surfaces (Ramsay and Silverman, 2002, 2005).”
Second-Order Comparison of Gaussian Random Functions and the Geometry of DNA Minicircles (2010, methodology): “…by an “optimal” reduction to a finite-dimensional setting, using finitely many appropriately chosen contrasts in a functional principal component analysis (e.g., Ramsay and Silverman 2002, 2005; Hall and Hosseini-Nasab 2006; also see Dauxois, Pousse, and Romain 1982 for distributional asymptotics).”
When to Use Hierarchical Linear Modeling (2014, methodology): “Developed by Ramsay and Silverman (2002, 2005), FDA is used specifically for longitudinal data.”
Canonical correlation for stochastic processes (2008, background): “[27] J. Ramsay, B. Silverman, Functional Data Analysis, Springer, 1997.”
Functional Convex Averaging and Synchronization for Time-Warped Random Curves (2004, methodology): “Here the proposed model and algorithm are compared with other registration methods, using the Berkeley growth study (Ramsay and Silverman 2002, Chap.”
On rates of convergence in functional linear regression (2007, background): “The books Ramsay and Silverman [15,16,20] and their website “http://ego.psych.mcgill.ca/misc/fda” contain a substantial amount of information in that regard.”
Functional linear regression with derivatives (2006, background): “Now we are ready to go back to (22) and (23) as announced sooner.”