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 1461 articles , 1 standard article )

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  1. Almanjahie, Ibrahim M.; Bouzebda, Salim; Chikr Elmezouar, Zouaoui; Laksaci, Ali: The functional (k\mathrmNN) estimator of the conditional expectile: uniform consistency in number of neighbors (2022)
  2. Amel, Azzi; Ali, Laksaci; Elias, Ould Saïd: On the robustification of the kernel estimator of the functional modal regression (2022)
  3. Aneiros, Germán; Novo, Silvia; Vieu, Philippe: Variable selection in functional regression models: a review (2022)
  4. Benth, Fred Espen; Schroers, Dennis; Veraart, Almut E. D.: A weak law of large numbers for realised covariation in a Hilbert space setting (2022)
  5. Düker, Marie-Christine; Pipiras, Vladas; Sundararajan, Raanju: Cotrending: testing for common deterministic trends in varying means model (2022)
  6. Golovkine, Steven; Klutchnikoff, Nicolas; Patilea, Valentin: Clustering multivariate functional data using unsupervised binary trees (2022)
  7. Levantesi, Susanna; Nigri, Andrea; Piscopo, Gabriella: Clustering-based simultaneous forecasting of life expectancy time series through Long-Short Term Memory Neural Networks (2022)
  8. Liu, Xi; Divani, Afshin A.; Petersen, Alexander: Truncated estimation in functional generalized linear regression models (2022)
  9. Li, Yehua; Qiu, Yumou; Xu, Yuhang: From multivariate to functional data analysis: fundamentals, recent developments, and emerging areas (2022)
  10. Samaddar, Arunava; Jackson, Brooke S.; Helms, Christopher J.; Lazar, Nicole A.; McDowell, Jennifer E.; Park, Cheolwoo: A group comparison in fMRI data using a semiparametric model under shape invariance (2022)
  11. Smida, Zaineb; Cucala, Lionel; Gannoun, Ali; Durif, Ghislain: A Wilcoxon-Mann-Whitney spatial scan statistic for functional data (2022)
  12. Telschow, Fabian J. E.; Schwartzman, Armin: Simultaneous confidence bands for functional data using the Gaussian kinematic formula (2022)
  13. Tong, Hongzhi: Distributed least squares prediction for functional linear regression (2022)
  14. Tong, Hongzhi: Convergence rates of support vector machines regression for functional data (2022)
  15. Torti, Agostino; Galvani, Marta; Menafoglio, Alessandra; Secchi, Piercesare; Vantini, Simone: A general bi-clustering algorithm for object data with an application to the analysis of a Lombardy railway line (2022)
  16. Wang, Jiangyan; Gu, Lijie; Yang, Lijian: Oracle-efficient estimation for functional data error distribution with simultaneous confidence band (2022)
  17. Xu, Jianjun; Cui, Wenquan: A new RKHS-based global testing for functional linear model (2022)
  18. 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)
  19. Bertin, Karine; Klutchnikoff, Nicolas: Adaptive regression with Brownian path covariate (2021)
  20. Beyaztas, Ufuk; Shang, Han Lin: A partial least squares approach for function-on-function interaction regression (2021)

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