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  • Tutorial
  • Examples
  • API Reference
  • Citing scikit-fda
  • Glossary
  • Contributors ✨
  • GitHub
  • PyPI
  • Anaconda

Section Navigation

  • Boxplot
  • Classification methods
  • Clustering
  • Depth based classification
  • Discretized function representation
  • Elastic registration
  • Exploring data
  • Extrapolation
  • Function composition
  • Functional Diffusion Maps
  • Functional Linear Regression with multivariate covariates.
  • Functional Principal Component Analysis
  • Functional Principal Component Analysis Regression.
  • Interpolation
  • K-nearest neighbors classification
  • Kernel Regression
  • Kernel Smoothing
  • Landmark registration
  • Landmark shift
  • Magnitude-Shape Plot
  • Magnitude-Shape Plot synthetic example
  • Meteorological data: data visualization, clustering, and functional PCA
  • Mixed effects model for irregular data
  • Mixed effects model for irregular data: robustness of the conversion by decimation
  • Neighbors Functional Regression
  • Neighbors Scalar Regression
  • One-way functional ANOVA with real data
  • One-way functional ANOVA with synthetic data
  • Outlier detection with FPCA
  • Pairwise alignment
  • Radius neighbors classification
  • Representation of functional data
  • SDE simulation: Langevin dynamics
  • SDE simulation: creating synthetic datasets using SDEs
  • Shift Registration
  • Spectrometric data: derivatives, regression, and variable selection
  • Surface Boxplot
  • Voice signals: smoothing, registration, and classification
  • Expand scikit-fda
    • Creating a new basis
    • Creating a new interpolation or extrapolation strategy
  • Examples
  • Expand scikit-fda

Expand scikit-fda#

Examples of how to expand the functionality of scikit-fda with custom behaviors.

Creating a new basis

Creating a new basis

Creating a new interpolation or extrapolation strategy

Creating a new interpolation or extrapolation strategy

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Voice signals: smoothing, registration, and classification

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Creating a new basis

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