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 744 articles , 1 standard article )

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  1. Aneiros, Germán; Vieu, Philippe: Comments on: “Probability enhanced effective dimension reduction for classifying sparse functional data” (2016)
  2. Attaoui, Said; Ling, Nengxiang: Asymptotic results of a nonparametric conditional cumulative distribution estimator in the single functional index modeling for time series data with applications (2016)
  3. Benhenni, Karim; Su, Yingcai: Optimal sampling designs for nonparametric estimation of spatial averages of random fields (2016)
  4. Benziadi, Fatima; Laksaci, Ali; Tebboune, Fethallah: Note on conditional quantiles for functional ergodic data (2016)
  5. Beran, Jan; Liu, Haiyan: Estimation of eigenvalues, eigenvectors and scores in FDA models with dependent errors (2016)
  6. Beran, Jan; Liu, Haiyan; Telkmann, Klaus: On two sample inference for eigenspaces in functional data analysis with dependent errors (2016)
  7. Berkes, István; Horváth, Lajos; Rice, Gregory: On the asymptotic normality of kernel estimators of the long run covariance of functional time series (2016)
  8. Berrendero, José R.; Cuevas, Antonio; Pateiro-López, Beatriz: Shape classification based on interpoint distance distributions (2016)
  9. Blanke, D.; Bosq, D.: Detecting and estimating intensity of jumps for discretely observed $\operatornameARMAD(1,1)$ processes (2016)
  10. Bodnar, Taras; Gupta, Arjun K.; Parolya, Nestor: Direct shrinkage estimation of large dimensional precision matrix (2016)
  11. Bohorquez, Martha; Giraldo, Ramón; Mateu, Jorge: Optimal sampling for spatial prediction of functional data (2016)
  12. Boj, Eva; Caballé, Adrià; Delicado, Pedro; Esteve, Anna; Fortiana, Josep: Global and local distance-based generalized linear models (2016)
  13. Boudou, Alain; Viguier-Pla, Sylvie: Gap between orthogonal projectors -- application to stationary processes (2016)
  14. Brunel, Élodie; Mas, André; Roche, Angelina: Non-asymptotic adaptive prediction in functional linear models (2016)
  15. Chiou, Jeng-Min; Yang, Ya-Fang; Chen, Yu-Ting: Multivariate functional linear regression and prediction (2016)
  16. Choroś-Tomczyk, Barbara; Härdle, Wolfgang Karl; Okhrin, Ostap: A semiparametric factor model for CDO surfaces dynamics (2016)
  17. Collazos, Julian A.A.; Dias, Ronaldo; Zambom, Adriano Z.: Consistent variable selection for functional regression models (2016)
  18. Crambes, Christophe; Hilgert, Nadine; Manrique, Tito: Estimation of the noise covariance operator in functional linear regression with functional outputs (2016)
  19. Dabo-Niang, S.; Guillas, S.; Ternynck, C.: Efficiency in multivariate functional nonparametric models with autoregressive errors (2016)
  20. Demongeot, Jacques; Hamie, Ali; Laksaci, Ali; Rachdi, Mustapha: Relative-error prediction in nonparametric functional statistics: theory and practice (2016)

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