robfpca-package: robfpca: Functional principal component analysis for...
In statKim/robfpca: Functional principal component analysis for partially observed elliptical process
robfpca-package R Documentation
robfpca: Functional principal component analysis for partially observed elliptical process
Description
Robust functional principal component analysis (FPCA) for partially observed functional data. It is based on the pairwise robust covariance function estimation and eigenanalysis. The location and scale functions are computed via pointwise M-estimator, and the covariance function is obtained via robust pairwise computation based on Orthogonalized Gnanadesikan-Kettenring (OGK) estimation. Additionally, bivariate Nadaraya-Watson smoothing is applied for smoothed covariance surfaces. To deal with the missing segments, FPCA is performed via PACE (Principal Analysis via Conditional Expectation).
Author(s)
Maintainer: Hyunsung Kim hyunsung1021@gmail.com
Authors:
Yeonjoo Park
Yaeji Lim
statKim/robfpca documentation built on April 15, 2023, 10:12 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
| robfpca-package | R Documentation |
robfpca: Functional principal component analysis for partially observed elliptical process
Description
Robust functional principal component analysis (FPCA) for partially observed functional data. It is based on the pairwise robust covariance function estimation and eigenanalysis. The location and scale functions are computed via pointwise M-estimator, and the covariance function is obtained via robust pairwise computation based on Orthogonalized Gnanadesikan-Kettenring (OGK) estimation. Additionally, bivariate Nadaraya-Watson smoothing is applied for smoothed covariance surfaces. To deal with the missing segments, FPCA is performed via PACE (Principal Analysis via Conditional Expectation).
Author(s)
Maintainer: Hyunsung Kim hyunsung1021@gmail.com
Authors:
Yeonjoo Park
Yaeji Lim
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.