S3 Classes and Methods for Tidy Functional Data
Convert functional data back to tabular data formats
Turns any object into a list
Eigenfunctions via weighted, regularized SVD
Summarize each tf in a vector
Find out if values are inside given bounds
Preprocess evaluation grid for plotting
tf: S3 Classes and Methods for Tidy Functional Data
Inter- and extrapolation functions for tfd-objects
Functional Data Depth
Differentiating functional data: approximating derivative functions
Evaluate tf-vectors for given argument values
Integrals and anti-derivatives of functional data
Re-evaluate tf-objects on a new grid of argument values.
Make a tf (more) irregular
Change (basis) representation of a tf-object
Gaussian Process random generator
Simple smoothing of tf objects
Find out where functional data fulfills certain conditions.
Functions to zoom in/out on functions
Constructors for functional data in basis representation
Functional data in FPC-basis representation
Spline-based representation of functional data
Accessing, evaluating, subsetting and subassigning tf vectors
Constructors for vectors of "raw" functional data
Pretty printing and formatting for functional data
Math, Summary and Ops Methods for tf
Utility functions for tf-objects
Functions that summarize tf objects across argument values
base plots for tfs
Make syntactically valid unique names
vctrs methods for tf objects
Defines S3 vector data types for vectors of functional data (grid-based, spline-based or functional principal components-based) with all arithmetic and summary methods, derivation, integration and smoothing, plotting, data import and export, and data wrangling, such as re-evaluating, subsetting, sub-assigning, zooming into sub-domains, or extracting functional features like minima/maxima and their locations. The implementation allows including such vectors in data frames for joint analysis of functional and scalar variables.
Useful links