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funpca  

Functional Principal Component Analysis
View on CRAN: Click here


Download and install funpca package within the R console
Install from CRAN:
install.packages("funpca")

Install from Github:
library("remotes")
install_github("cran/funpca")

Install by package version:
library("remotes")
install_version("funpca", "9.0")



Attach the package and use:
library("funpca")
Maintained by
Francisco Rosales
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-06-15
Latest Update: 2023-06-15
Description:
Functional principal component analysis under the Linear Mixed Models representation of smoothing splines. The method utilizes the Demmler-Reinsch basis and assumes error independence. For more details see: F. Rosales (2016) .
How to cite:
Francisco Rosales (2023). funpca: Functional Principal Component Analysis. R package version 9.0, https://cran.r-project.org/web/packages/funpca. Accessed 22 Dec. 2024.
Previous versions and publish date:
No previous versions
Other packages that cited funpca R package
View funpca citation profile
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Complete documentation for funpca
Functions, R codes and Examples using the funpca R package
Some associated functions: funpca-internal . funpca-package . funpca . plot.funpca . summary.funpca . 
Some associated R codes: Sqrt.R . dbind.R . drbasis.R . funpca.R . funpca.default.R . funpcaEst.R . globals.R . plot.funpca.R . print.funpca.R . spectralnorm.R . summary.funpca.R .  Full funpca package functions and examples
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