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fda (version 1.1.4)

Functional Data Analysis

Description

These functions were developed to support functional data analysis as described in Ramsay, J. O. and Silverman, B. W. (2005) Functional Data Analysis. New York: Springer. They were ported from earlier versions in Matlab and S-PLUS. A manual that describes the use of these functions is available in this library. The library also contains a number of the data sets used in the book along with R code for the analyses that produced many of the figures in the book.

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Version

Install

install.packages('fda')

Monthly Downloads

14,245

Version

1.1.4

License

GPL version 2 or later

Maintainer

S by Jim Ramsey

Last Published

September 17th, 2024

Functions in fda (1.1.4)

Define a Linear Differential Operator Object

Computes Cross-validated Error Sum of Squares for a Functional Regression Model

Exponential Basis Function Values

create.bspline.basis

Create a B-spline Basis

getbasispenalty

Evaluate a Roughness Penalty Matrix

Evaluate Monomial Roughness Penalty Matrix

Polygonal Penalty Matrix

Plot a Functional Data Object With Data

Fourier Penalty Matrix

Mean of Functional Data

Inner products of Functional Data Objects.

Power Penalty Matrix

Estimates a Smooth Warping Function

Convert Degrees of Freedom to a Smoothing Parameter Value

Values a Two-argument Functional Data Object

Standard Deviation of Functional Data

Fit Fully Functional Linear Model

Define a Functional Parameter Object

Approximate Functional Data Using a Basis

Functional Principal Components Analysis

Evaluate the Diagonal of a Bivariate Functional Data Object

Smooth a Functional Data Object Using a Roughness Penalty

Fourier Basis Function Values

Compute GCV Criterion

create.polygonal.basis

Create a Polygonal Basis

Confirm Object is Class "Basisfd"

A Functional Regression Analysis of the Concurrent Type

Values of Basis Functions or their Derivatives

Plot Cycles for a Periodic Bivariate Functional Data Object

Intensity Function for Point Process

Principal Differential Analysis

Rotation of Functional Canonical Components with VARIMAX

Register Functional Data Objects Using a Continuous Criterion

Functional Canonical Correlation Analysis

Compute Inner Products B-spline Expansions.

Summarize a Linear Differential Operator Object

Evaluate Monomial Basis

Plot a Functional Data Object

Rotation of Functional Principal Components with VARIMAX Criterion

Confirm Object has Class "fd"

Smooth Data with a Positive Function

Compute a Derivative of a Functional Data Object

create.polynomial.basis

Create a Polynomial Basis

Variance and Covariance Surfaces for a Functional Data Object

Values of Basis Functions or their Derivatives

create.exponential.basis

Create an Exponential Basis

Values of a Functional Data Object

B-Spline Penalty Matrix

Compute a Probability Density Function

Sum of Functional Data

Define a Functional Data Object

Convert Discrete Data to Functional Data

Exponential Penalty Matrix

Center Functional Data

B-spline Basis Function Values

Convert Integer to Linear Differential Operator

fRegress.stderr

Compute Standard errors of Coefficient Functions Estimated by Functional Regression Analysis

Values of a Monotone Functional Data Object

Numerical Solution mth Order Differential Equation System

Power Basis Function Values

Landmark Registration of Functional Observations

Add Lines from Functional Data to a Plot

Convert Smoothing Parameter to Degrees of Freedom

Confirm Object has Class "fdPar"

Rotate a Matrix of Component Loadings using the VARIMAX Criterion

Standard Deviation of Functional Data

Polygonal Basis Function Values

create.monomial.basis

Create a Monomial Basis

Smooth Data with a Roughness Penalty

Evaluate a Basis Penalty Matrix

create.fourier.basis

Create a Fourier Basis

create.constant.basis

Create a Constant Basis

Plot a Basis Object

Evaluate a Positive Functional Data Object

Confirm Object has Class "Lfd"

Summarize a Functional Data Object

Summarize a Bivariate Functional Data Object

smooth.monotone

Monotone Smoothing of Data

Summarize a Functional Parameter Object

create.power.basis

Create a Power Basis Object

Define a Functional Basis Object

Make a Linear Differential Operator Object from a Vector

Plot Principal Component Scores