# fda v2.4.4

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## Functional Data Analysis

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. An
introduction appears 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 of the code and
sample analyses are no longer distributed through CRAN, as they
were when the book was published. For those, ftp from
http://www.psych.mcgill.ca/misc/fda/downloads/FDAfuns/
There you find a set of .zip files containing the functions and
sample analyses, as well as two .txt files giving instructions for
installation and some additional information.
The changes from Version 2.4.1 are fixes of bugs in density.fd and
removal of functions create.polynomial.basis, polynompen, and
polynomial. These were deleted because the monomial basis
does the same thing and because there were errors in the code.

## Functions in fda

Name | Description | |

as.POSIXct1970 | as.POXIXct for number of seconds since the start of 1970. | |

as.fd | Convert a spline object to class 'fd' | |

df.residual.fRegress | Degress of Freedom for Residuals from a Functional Regression | |

eval.monfd | Values of a Monotone Functional Data Object | |

monfn | Evaluates a monotone function | |

fdaMatlabPath | Add 'fdaM' to the Matlab path | |

Fstat.fd | F-statistic for functional linear regression. | |

ReginaPrecip | Regina Daily Precipitation | |

polygpen | Polygonal Penalty Matrix | |

argvalsy.swap | Swap argvals with y if the latter is simpler. | |

TaylorSpline | Taylor representation of a B-Spline | |

lines.fd | Add Lines from Functional Data to a Plot | |

Eigen | Eigenanalysis preserving dimnames | |

density.fd | Compute a Probability Density Function | |

MontrealTemp | Montreal Daily Temperature | |

intensity.fd | Intensity Function for Point Process | |

arithmetic.fd | Arithmetic on functional data ('fd') objects | |

exponpen | Exponential Penalty Matrix | |

plot.Lfd | Plot a Linear Differential Operator Object | |

cca.fd | Functional Canonical Correlation Analysis | |

smooth.pos | Smooth Data with a Positive Function | |

bifdPar | Define a Bivariate Functional Parameter Object | |

create.bspline.basis | Create a B-spline Basis | |

refinery | Reflux and tray level in a refinery | |

create.exponential.basis | Create an Exponential Basis | |

dateAccessories | Numeric and character vectors to facilitate working with dates | |

dirs | Get subdirectories | |

eval.basis | Values of Basis Functions or their Derivatives | |

fd2list | Convert a univariate functional data object to s list | |

int2Lfd | Convert Integer to Linear Differential Operator | |

linmod | Fit Fully Functional Linear Model | |

eval.bifd | Values a Two-argument Functional Data Object | |

summary.basisfd | Summarize a Functional Data Object | |

eval.posfd | Evaluate a Positive Functional Data Object | |

is.basis | Confirm Object is Class "Basisfd" | |

handwrit | Cursive handwriting samples | |

lmWinsor12 | Support functions for lmWinsor | |

create.monomial.basis | Create a Monomial Basis | |

create.constant.basis | Create a Constant Basis | |

plotbeta | Plot a functional parameter object with confidence limits | |

cor.fd | Correlation matrix from functional data object(s) | |

is.fd | Confirm Object has Class "fd" | |

sd.fd | Standard Deviation of Functional Data | |

symsolve | solve(A, B) where A is symmetric | |

knots.fd | Extract the knots from a function basis or data object | |

fbplot | Functional Boxplots | |

register.fd0 | Correct for initial position error between functional data objects. | |

summary.bifd | Summarize a Bivariate Functional Data Object | |

lip | Lip motion | |

fRegress.CV | Computes Cross-validated Error Sum of Integrated Squared Errors for a Functional Regression Model | |

seabird | Sea Bird Counts | |

fRegress.stderr | Compute Standard errors of Coefficient Functions Estimated by Functional Regression Analysis | |

center.fd | Center Functional Data | |

eval.penalty | Evaluate a Basis Penalty Matrix | |

fd | Define a Functional Data Object | |

file.copy2 | Copy a file with a default 'to' name | |

getbasismatrix | Values of Basis Functions or their Derivatives | |

axisIntervals | Mark Intervals on a Plot Axis | |

plot.pca.fd | Plot Functional Principal Components | |

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

create.fourier.basis | Create a Fourier Basis | |

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

evaldiag.bifd | Evaluate the Diagonal of a Bivariate Functional Data Object | |

matplot | Plot Columns of Matrices | |

onechild | growth in height of one 10-year-old boy | |

norder | Order of a B-spline | |

melanoma | melanoma 1936-1972 | |

lmWinsor | Winsorized Regression | |

svd2 | singular value decomposition with automatic error handling | |

CanadianWeather | Canadian average annual weather cycle | |

fda-package | Functional Data Analysis in R | |

monomial | Evaluate Monomial Basis | |

Data2fd | Create a functional data object from data | |

Fperm.fd | Permutation F-test for functional linear regression. | |

residuals.fRegress | Residuals from a Functional Regression | |

geigen | Generalized eigenanalysis | |

bifd | Create a bivariate functional data object | |

create.power.basis | Create a Power Basis Object | |

create.polygonal.basis | Create a Polygonal Basis | |

plot.basisfd | Plot a Basis Object | |

register.fd | Register Functional Data Objects Using a Continuous Criterion | |

plot.lmWinsor | lmWinsor plot | |

smooth.monotone | Monotone Smoothing of Data | |

summary.fd | Summarize a Functional Data Object | |

register.newfd | Register Functional Data Objects with Pre-Computed Warping Functions | |

checkLogicalInteger | Does an argument satisfy required conditions? | |

nondurables | Nondurable goods index | |

objAndNames | Add names to an object | |

cycleplot.fd | Plot Cycles for a Periodic Bivariate Functional Data Object | |

predict.fRegress | Predict method for Functional Regression | |

exponentiate.fd | Powers of a functional data ('fd') object | |

fourierpen | Fourier Penalty Matrix | |

smooth.bibasis | Smooth a discrete surface over a rectangular lattice | |

is.fdSmooth | Confirm Object has Class "fdSmooth" | |

CSTR | Continuously Stirred Tank Reactor | |

is.fdPar | Confirm Object has Class "fdPar" | |

lambda2df | Convert Smoothing Parameter to Degrees of Freedom | |

inprod | Inner products of Functional Data Objects. | |

getbasispenalty | Evaluate a Roughness Penalty Matrix | |

is.Lfd | Confirm Object has Class "Lfd" | |

fdlabels | Extract plot labels and names for replicates and variables | |

expon | Exponential Basis Function Values | |

odesolv | Numerical Solution mth Order Differential Equation System | |

basisfd | Define a Functional Basis Object | |

mean.fd | Mean of Functional Data | |

predict.lmeWinsor | Predict method for Winsorized linear model fits with mixed effects | |

fourier | Fourier Basis Function Values | |

zerofind | Does the range of the input contain 0? | |

pda.fd | Principal Differential Analysis | |

varmx | Rotate a Matrix of Component Loadings using the VARIMAX Criterion | |

polyg | Polygonal Basis Function Values | |

smooth.fd | Smooth a Functional Data Object Using an Indirectly Specified Roughness Penalty | |

as.array3 | Reshape a vector or array to have 3 dimensions. | |

quadset | Quadrature points and weights for Simpson's rule | |

summary.fdPar | Summarize a Functional Parameter Object | |

gait | Hip and knee angle while walking | |

varmx.cca.fd | Rotation of Functional Canonical Components with VARIMAX | |

powerpen | Power Penalty Matrix | |

powerbasis | Power Basis Function Values | |

basisfd.product | Product of two basisfd objects | |

landmark.reg.expData | Experiment data for landmark registration and alignment | |

smooth.basisPar | Smooth Data Using a Directly Specified Roughness Penalty | |

phaseplanePlot | Phase-plane plot | |

var.fd | Variance, Covariance, and Correlation Surfaces for Functional Data Object(s) | |

plotscores | Plot Principal Component Scores | |

pca.fd | Functional Principal Components Analysis | |

coef.fd | Extract functional coefficients | |

vec2Lfd | Make a Linear Differential Operator Object from a Vector | |

bsplineS | B-spline Basis Function Values | |

sum.fd | Sum of Functional Data | |

monomialpen | Evaluate Monomial Roughness Penalty Matrix | |

fRegress | Functional Regression Analysis | |

eval.fd | Values of a Functional Data Object | |

AmpPhaseDecomp | Decomposition for Amplitude and Phase Variation | |

smooth.fdPar | Smooth a functional data object using a directly specified roughness penalty | |

fdPar | Define a Functional Parameter Object | |

inprod.bspline | Compute Inner Products B-spline Expansions. | |

lambda2gcv | Compute GCV Criterion | |

lmeWinsor | Winsorized Regression with mixed effects | |

plotfit | Plot a Functional Data Object With Data | |

Lfd | Define a Linear Differential Operator Object | |

arithmetic.basisfd | Arithmatic on functional basis objects | |

CRAN | Test if running as CRAN | |

StatSciChinese | Statistical Science in Chinese | |

checkDims3 | Compare dimensions and dimnames of arrays | |

df2lambda | Convert Degrees of Freedom to a Smoothing Parameter Value | |

growth | Berkeley Growth Study data | |

infantGrowth | Tibia Length for One Baby | |

project.basis | Approximate Functional Data Using a Basis | |

plot.fd | Plot a Functional Data Object | |

readHMD | Download data from the Human Mortality Database (HMD) | |

smooth.basis | Construct a functional data object by smoothing data using a roughness penalty | |

varmx.pca.fd | Rotation of Functional Principal Components with VARIMAX Criterion | |

pda.overlay | Stability Analysis for Principle Differential Analysis | |

bsplinepen | B-Spline Penalty Matrix | |

getbasisrange | Extract the range from a basis object | |

predict.lmWinsor | Predict method for Winsorized linear model fits | |

smooth.morph | Estimates a Smooth Warping Function | |

summary.Lfd | Summarize a Linear Differential Operator Object | |

create.basis | Create Basis Set for Functional Data Analysis | |

deriv.fd | Compute a Derivative of a Functional Data Object | |

landmarkreg | Landmark Registration of Functional Observations | |

wtcheck | Check a vector of weights | |

pinch | pinch force data | |

No Results! |

## Last month downloads

## Details

Date | 2014.05.03 |

License | GPL (>= 2) |

URL | http://www.functionaldata.org |

LazyData | true |

Repository | CRAN |

Repository/R-Forge/Project | fda |

Repository/R-Forge/Revision | 761 |

Repository/R-Forge/DateTimeStamp | 2014-12-10 23:04:14 |

Date/Publication | 2014-12-16 17:59:38 |

Packaged | 2014-12-10 23:25:10 UTC; rforge |

NeedsCompilation | no |

depends | base (>= 2.10.0) , graphics , Matrix , R (>= 2.10.0) , splines |

suggests | deSolve , lattice , nlme , quadprog , R.matlab , RCurl , zoo |

Contributors | Giles Hooker, S by Jim Ramsey, Hadley Wickham, Spencer Graves |

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