This package provides the tools to perform the functional data analysis. The core of this package is functional principal componet analysis (FPCA) based on the principal analysis by conditional estimation (PACE) algorithm mainly developed by H.G. Muller. The multivariate part with normalization are done primarily by J.M. Chiou, Y.F Yang, and Y.T. Chen (See References). In addition, this package provides the another normalization approach (with quantiles) in multivariate FPCA. This package is mostly based on the MatLab package, PACE, released at http://www.stat.ucdavis.edu/PACE/. Besides, some ideas are borrowed from the R package, fdapace. This package, rfda, provides R approach for FPCA based on PACE 2.17 and use the C++ linear algebra library, Armadillo, and the C++ multi-threaded implementation with RcppArmadillo and RcppParallel. Note: Since the BLAS used by RcppArmadillo is based on what BLAS R links to, so this package will be more efficient if a powerful BLAS used by R.
|Author||Ching-Chuan Chen [aut, cre]|
|Maintainer||Ching-Chuan Chen <[email protected]>|
|License||BSD_3_clause + file LICENSE|
|Package repository||View on GitHub|
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