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fda (version 6.0.5)

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 and in Ramsay, J. O., Hooker, Giles, and Graves, Spencer (2009). Functional Data Analysis with R and Matlab (Springer). The package includes data sets and script files working many examples including all but one of the 76 figures in this latter book. Matlab versions are available by ftp from .

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Version

Install

install.packages('fda')

Monthly Downloads

17,533

Version

6.0.5

License

GPL (>= 2)

Maintainer

S by Jim Ramsey

Last Published

July 4th, 2022

Functions in fda (6.0.5)

Create a functional data object from data

Predicting electricity demand in Adelaide from temperature

Test if running as CRAN

CanadianWeather

Canadian average annual weather cycle

F-statistic for functional linear regression.

Define a Linear Differential Operator Object

Decomposition for Amplitude and Phase Variation

Permutation F-test for functional linear regression.

Continuously Stirred Tank Reactor

Eigenanalysis preserving dimnames

Reshape a vector or array to have 3 dimensions.

Mark Intervals on a Plot Axis

Convert a spline object to class 'fd'

Montreal Daily Temperature

Statistical Science in Chinese

arithmetic.basisfd

Arithmatic on functional basis objects

Arithmetic on functional data ('fd') objects

as.POXIXct for number of seconds since the start of 1970.

Regina Daily Precipitation

Define a Bivariate Functional Parameter Object

basisfd.product

Product of two basisfd objects

B-spline Basis Function Values

Extract functional coefficients

checkLogicalInteger

Does an argument satisfy required conditions?

Create a bivariate functional data object

Compare dimensions and dimnames of arrays

Center Functional Data

Define a Functional Basis Object

Functional Canonical Correlation Analysis

create.polygonal.basis

Create a Polygonal Basis

Correlation matrix from functional data object(s)

create.constant.basis

Create a Constant Basis

B-Spline Penalty Matrix

Create Basis Set for Functional Data Analysis

create.power.basis

Create a Power Basis Object

create.monomial.basis

Create a Monomial Basis

create.fourier.basis

Create a Fourier Basis

create.exponential.basis

Create an Exponential Basis

Estimate of the covariance surface

Convert Degrees of Freedom to a Smoothing Parameter Value

create.bspline.basis

Create a B-spline Basis

Values of Basis Functions or their Derivatives

Stability Analysis for Principle Differential Analysis

dateAccessories

Numeric and character vectors to facilitate working with dates

Compute a Probability Density Function

Compute a Derivative of a Functional Data Object

Values of a Functional Data Object Defining Surprisal Curves.

Evaluate a Positive Functional Data Object

Get subdirectories

Compute a Cumulative Distribution Functional Data Object

Values a Two-argument Functional Data Object

df.residual.fRegress

Degrees of Freedom for Residuals from a Functional Regression

Values of a Functional Data Object

Exponential Basis Function Values

Evaluate the Diagonal of a Bivariate Functional Data Object

exponentiate.fd

Powers of a functional data ('fd') object

Exponential Penalty Matrix

Plot Cycles for a Periodic Bivariate Functional Data Object

Define a Functional Data Object

Functional Regression Analysis

Computes Cross-validated Error Sum of Integrated Squared Errors for a Functional Regression Model

Define a Functional Parameter Object

Convert fd or basisfd Objects to fdPar Objects

Cursive handwriting samples

Convert a univariate functional data object to a list

Hip and knee angle while walking

Tibia Length for One Baby

Extract plot labels and names for replicates and variables

Functional Data Analysis in R

Fourier Basis Function Values

Confirm Object has Class "Lfd"

Confirm Object is Class "Basisfd"

Generalized eigenanalysis

Compute Inner Products B-spline Expansions.

Inner products of Functional Data Objects.

Berkeley Growth Study data

Extract the range from a basis object

Confirm that two objects of class "Basisfd" are identical

Fourier Penalty Matrix

Confirm Object has Class "fdPar"

Confirm Object has Class "fd"

Confirm Object has Class "fdSmooth"

Plot Columns of Matrices

Intensity Function for Point Process

Convert Integer to Linear Differential Operator

Values of a Monotone Functional Data Object

Mean of Functional Data

Evaluate a Basis Penalty Matrix

Extract the knots from a function basis or data object

Convert Smoothing Parameter to Degrees of Freedom

Evaluate the gradient of a monotone function

fRegress.stderr

Compute Standard errors of Coefficient Functions Estimated by Functional Regression Analysis

Evaluate Monomial Basis

Evaluate the Hessian matrix of a monotone function

pinch force data

Evaluate Monomial Roughness Penalty Matrix

Phase-plane plot

Search along a line for a minimum within an optimisation algorithm.

Plot a Basis Object

Plot a Linear Differential Operator Object

melanoma 1936-1972

Plot Functional Principal Components

Functional Boxplots

Evaluate the a monotone function

Plot Principle Differential Analysis Components

Polynomial extrapolation for a converging sequence of one or more values

Polygonal Basis Function Values

Estimates of functional Principal Component scores through PACE

Values of Basis Functions or their Derivatives

Add Lines from Functional Data to a Plot

getbasispenalty

Evaluate a Roughness Penalty Matrix

Standard Deviation of Functional Data

predict.fRegress

Predict method for Functional Regression

Estimate the functional principal components

Functional Principal Components Analysis

Approximate Functional Data Using a Basis

Register Functional Data Objects with Pre-Computed Warping Functions

Register Functional Data Objects Using a Continuous Criterion

Quadrature points and weights for Simpson's rule

Power Basis Function Values

Polygonal Penalty Matrix

Add names to an object

Fit Fully Functional Linear Model

Estimates a Smooth Warping Function Mapping an Interval into Another

Numerical Solution mth Order Differential Equation System

Sea Bird Counts

Compute GCV Criterion

Landmark Registration of Functional Observations with Differing Ranges

Nondurable goods index

Sum of Functional Data

Construct a functional data object by smoothing data using a roughness penalty

Approximate the functional inner product of two functional data objects using the trapezpoidal rule over a fine mesh of value.

Permutation t-test for two groups of functional data objects.

Summarize a Functional Parameter Object

Summarize a Linear Differential Operator Object

Summarize a Functional Data Object

Reconstruct data curves using functional principal components

Principal Differential Analysis

Order of a B-spline

Smooth a Functional Data Object Using an Indirectly Specified Roughness Penalty

Smooth a discrete surface over a rectangular lattice

Plot Functional Canonical Correlation Weight Functions

Stability Analysis for Principle Differential Analysis

Smooth Data with a Positive Function

Plot a functional parameter object with confidence limits

Plot a Functional Data Object

Plot a Functional Data Object With Data

Check a vector of weights

Make a Linear Differential Operator Object from a Vector

Check a step size value for being within parameter limits.

Plot the results of the registration of a set of curves

smooth.monotone

Monotone Smoothing of Data

Smooth a functional data object using a directly specified roughness penalty

smooth.sparse.mean

Smooth the mean function of sparse data

Fit data with surprisal smoothing.

summary.basisfd

Summarize a Functional Data Object

Compute a new step size for a linear search within an optimization algorithm.

Plot Principal Component Scores

Variance, Covariance, and Correlation Surfaces for Functional Data Object(s)

Evaluate the fit of surprisal curves to binned psychometric data.

Rotate a Matrix of Component Loadings using the VARIMAX Criterion

Power Penalty Matrix

solve(A, B) where A is symmetric

Summarize a Bivariate Functional Data Object

smooth.basis.sparse

Construct a functional data object by smoothing data using a roughness penalty

Convert a B-spline function to piece-wise polynomial form

Creates a list of sparse data from a matrix

Creates a matrix of sparse data with NAs out of a list

Rotation of Functional Canonical Components with VARIMAX

smooth.basisPar

Smooth Data Using a Directly Specified Roughness Penalty

Check Data Arrays for Smoothing Functions

Rotation of Functional Principal Components with VARIMAX Criterion

Does the range of the input contain 0?

Orthonormal Matrix with Columns Summing to Zero