fda (R)

fda: Functional Data Analysis , These functions were developed to support functional data analysis as described in Ramsay, J. O. and Silverman, B. W. (2005) Functional Data Analysis. New York: Springer. They were ported from earlier versions in Matlab and S-PLUS. An introduction appears in Ramsay, J. O., Hooker, Giles, and Graves, Spencer (2009) Functional Data Analysis with R and Matlab (Springer). The package includes data sets and script files working many examples including all but one of the 76 figures in this latter book. As of this release, the R-Project is no longer distributing the Matlab versions of the functional data analysis functions and sample analyses through the CRAN distribution system. This is due to the pressure placed on storage required in the many CRAN sites by the rapidly increasing number of R packages, of which the fda package is one. The three of us involved in this package have agreed to help out this situation by switching to distributing the Matlab functions and analyses through Jim Ramsay’s ftp site at McGill University. To obtain these Matlab files, go to this site using an ftp utility: http://www.psych.mcgill.ca/misc/fda/downloads/FDAfuns/ There you find a set of .zip files containing the functions and sample analyses, as well as two .txt files giving instructions for installation and some additional information. (Source: http://cran.r-project.org/web/packages)

References in zbMATH (referenced in 1368 articles , 1 standard article )

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  1. Aguilera, Ana M.; Acal, Christian; Aguilera-Morillo, M. Carmen; Jiménez-Molinos, Francisco; Roldán, Juan B.: Homogeneity problem for basis expansion of functional data with applications to resistive memories (2021)
  2. Carey, M.; Ramsay, J. O.: Fast stable parameter estimation for linear dynamical systems (2021)
  3. Estévez-Pérez, Graciela; Vieu, Philippe: A new way for ranking functional data with applications in diagnostic test (2021)
  4. Evandro Konzen, Yafeng Cheng, Jian Qing Shi: Gaussian Process for Functional Data Analysis: The GPFDA Package for R (2021) arXiv
  5. Feng, Sanying; Tian, Ping; Hu, Yuping; Li, Gaorong: Estimation in functional single-index varying coefficient model (2021)
  6. Fermanian, Adeline: Embedding and learning with signatures (2021)
  7. Kolkiewicz, Adam; Rice, Gregory; Xie, Yijun: Projection pursuit based tests of normality with functional data (2021)
  8. Kounchev, O.; Render, H.: Error estimates for interpolation with piecewise exponential splines of order two and four (2021)
  9. Krebs, Johannes: A note on exponential inequalities in Hilbert spaces for spatial processes with applications to the functional kernel regression model (2021)
  10. Lai, Tingyu; Zhang, Zhongzhan; Wang, Yafei; Kong, Linglong: Testing independence of functional variables by angle covariance (2021)
  11. Li, Rui; Lu, Wenqi; Zhu, Zhongyi; Lian, Heng: Optimal prediction of quantile functional linear regression in reproducing kernel Hilbert spaces (2021)
  12. Mestre, Guillermo; Portela, José; Rice, Gregory; Muñoz San Roque, Antonio; Alonso, Estrella: Functional time series model identification and diagnosis by means of auto- and partial autocorrelation analysis (2021)
  13. Mohammedi, Mustapha; Bouzebda, Salim; Laksaci, Ali: The consistency and asymptotic normality of the kernel type expectile regression estimator for functional data (2021)
  14. Mohanty, Soumya D.; Fahnestock, Ethan: Adaptive spline fitting with particle swarm optimization (2021)
  15. Nagy, Stanislav; Helander, Sami; van Bever, Germain; Viitasaari, Lauri; Ilmonen, Pauliina: Flexible integrated functional depths (2021)
  16. Oluwasegun Ojo, Rosa E. Lillo, Antonio Fernández Anta: Outlier Detection for Functional Data with R Package fdaoutlier (2021) arXiv
  17. Pi, J.; Wang, Honggang; Pardalos, Panos M.: A dual reformulation and solution framework for regularized convex clustering problems (2021)
  18. Qiu, Zhiping; Chen, Jianwei; Zhang, Jin-Ting: Two-sample tests for multivariate functional data with applications (2021)
  19. Rennie, Nicola; Cleophas, Catherine; Sykulski, Adam M.; Dost, Florian: Identifying and responding to outlier demand in revenue management (2021)
  20. Rommel, Cédric; Bonnans, J. Frédéric; Gregorutti, Baptiste; Martinon, Pierre: Quantifying the closeness to a set of random curves via the mean marginal likelihood (2021)

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