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FDApy 1.0.3 documentation

  • Examples
  • API References
  • GitHub
  • PyPI
  • Examples
  • API References
  • GitHub
  • PyPI

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  • Representation
    • Representation of univariate and dense functional data
    • Representation of univariate and irregular functional data
    • Representation of functional data using a basis
    • Representation of multivariate functional data
  • Basis
    • One-dimensional Basis
    • Two-dimensional Basis
    • Multivariate Basis
  • Smoothing
    • Smoothing of dense one-dimensional functional data
    • Smoothing of dense two-dimensional functional data
  • Dimension Reduction
    • FPCA of 1-dimensional data
    • FPCA of 1-dimensional sparse data
    • FPCA of 2-dimensional data
    • MFPCA of 1-dimensional data
    • MFPCA of 2-dimensional data
    • MFPCA of 1- and 2-dimensional data
    • MFPCA of 1-dimensional sparse data
  • Real data analysis
    • Canadian weather dataset
    • CD4 dataset
  • Simulation
    • Simulation using Karhunen-Loève decomposition
    • Simulation using multivariate Karhunen-Loève decomposition
    • Simulation of Brownian motion
    • Simulation of functional data
    • Simulation of clusters of univariate functional data
    • Simulation of clusters of multivariate functional data
  • Miscellaneous
    • Smoothing of 1D data using local polynomial regression
    • Smoothing of 2D data using local polynomial regression
    • Smoothing of 1D data using P-Splines
    • Smoothing of 2D data using P-Splines
  • Examples
  • Smoothing

Smoothing#

These examples illustrate the use of the FDApy.preprocessing.smoothing module. It contains various functionalities to smooth functional data.

Smoothing of dense one-dimensional functional data

Smoothing of dense one-dimensional functional data

Smoothing of dense two-dimensional functional data

Smoothing of dense two-dimensional functional data

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Multivariate Basis

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Smoothing of dense one-dimensional functional data
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