• refund

  • Referenced in 63 articles [sw07434]
  • functional data using principal components. Functional principal components (FPC) analysis is widely used to decompose ... observations. Curve estimates implicitly condition on basis functions and other quantities derived from FPC decompositions ... constructed. Standard mixed model representations of functional expansions are used to construct curve estimates ... implemented to understand the uncertainty in principal component decomposition quantities. Our method compares favorably...
  • CGAL

  • Referenced in 384 articles [sw00118]
  • spheres, smallest enclosing ellipsoid of points, principal component analysis), and kinetic data structures. All these ... offers geometric object generators and spatial sorting functions, as well as a matrix search framework...
  • freqdom.fda

  • Referenced in 30 articles [sw36344]
  • Series: Dynamic Functional Principal Components. Implementations of functional dynamic principle components analysis. Related graphic tools ... principal components implementation, following the guidelines from Hormann, Kidzinski and Hallin (2016), Dynamic Functional Principal...
  • SuLQ

  • Referenced in 128 articles [sw11355]
  • First, we modify the privacy analysis to real-valued functions f and arbitrary row types ... very few invocations of the primitive: principal component analysis, k means clustering, the Perceptron Algorithm...
  • fdapace

  • Referenced in 7 articles [sw15968]
  • core of this package is Functional Principal Component Analysis (FPCA), a key technique for functional ... random trajectories and time courses, via the Principal Analysis by Conditional Estimation (PACE) algorithm...
  • fpca

  • Referenced in 5 articles [sw21039]
  • package fpca: Restricted MLE for Functional Principal Components Analysis. A geometric approach...
  • Eigenstrat

  • Referenced in 56 articles [sw33845]
  • EIGENSOFT package combines functionality from our population genetics methods (Patterson ... EIGENSTRAT method uses principal components analysis to explicitly model ancestry differences between cases and controls...
  • LIBRA

  • Referenced in 29 articles [sw10553]
  • LIBRA. LIBRA: a MATLAB Library for Robust Analysis is developed at ROBUST@Leuven, the research ... data. Currently, the library contains functions for univariate location, scale and skewness, multivariate location ... estimation (MCD), regression (LTS, MCD-regression), Principal Component Analysis (RAPCA, ROBPCA), Principal Component Regression (RPCR ... quantiles. For comparison also several non-robust functions are included. Many graphical tools are provided...
  • rsvd

  • Referenced in 7 articles [sw16104]
  • widely used for computing (randomized) principal component analysis (PCA), a linear dimensionality reduction technique. Randomized ... also includes a function to compute (randomized) robust principal component analysis (RPCA). In addition several...
  • PACE

  • Referenced in 3 articles [sw24632]
  • program of this package is Functional Principal Component Analysis (FPCA), a key technique for functional ... random trajectories and time courses, via the Principal Analysis by Conditional Estimation (PACE) algorithm...
  • MFPCA

  • Referenced in 3 articles [sw16091]
  • package MFPCA. Calculate a multivariate functional principal component analysis for data observed on different dimensional ... expansions for each element of the multivariate functional data. Multivariate and univariate functional data objects...
  • PACE

  • Referenced in 2 articles [sw28690]
  • core of this package is Functional Principal Component Analysis (FPCA), a key technique for functional ... random trajectories and time courses, via the Principal Analysis by Conditional Estimation (PACE) algorithm. PACE...
  • fChange

  • Referenced in 2 articles [sw36575]
  • Point Analysis in Functional Data. Change point estimation and detection methods for functional data ... implemented using dimension reduction via functional principal component analysis and a fully-functional (norm-based...
  • FUNNEL

  • Referenced in 2 articles [sw34200]
  • temporal information based on functional principal component analysis, and disentangles the effects of overlapping genes...
  • sparseFLMM

  • Referenced in 2 articles [sw21042]
  • sparsely sampled data based on functional principal component analysis...
  • funData

  • Referenced in 2 articles [sw21036]
  • oriented data analysis, it is shown why it is natural to implement functional data ... MFPCA package, which implements multivariate functional principal component analysis, is presented as an example...
  • GenForImp

  • Referenced in 2 articles [sw32731]
  • alternates Nearest Neighbour Imputation and Principal Component Analysis (function ’ForImp.PCA’), the other uses Nearest Neighbour...
  • amap

  • Referenced in 4 articles [sw19769]
  • Clustering and Principal Component Analysis (With robust methods, and parallelized functions...
  • LowRankModels

  • Referenced in 37 articles [sw27002]
  • models in data analysis, such as principal components analysis (PCA), matrix completion, robust PCA, nonnegative ... easy to mix and match loss functions and regularizers to construct a model suitable...
  • pcdpca

  • Referenced in 2 articles [sw26261]
  • Series. Method extends multivariate and functional dynamic principal components to periodically correlated multivariate time series ... allows you to compute true dynamic principal components in the presence of periodicity. We follow ... Jouzdani (2017), in Principal component analysis of periodically correlated functional time series...