Functional Data Analysis and Empirical Dynamics

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Documentation for package ‘fdapace’ version 0.5.9

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

BwNN	Minimum bandwidth based on kNN criterion.
CheckData	Check data format
CheckOptions	Check option format
ConvertSupport	Convert support of a mu/phi/cov etc. to and from obsGrid and workGrid
CreateBasis	Create an orthogonal basis of K functions in [0, 1], with nGrid points.
CreateBWPlot	Functional Principal Component Analysis Bandwidth Diagnostics plot
CreateCovPlot	Creates a correlation surface plot based on the results from FPCA() or FPCder().
CreateDesignPlot	Create design plots for functional data. See Yao, F., Müller, H.G., Wang, J.L. (2005). Functional data analysis for sparse longitudinal data. J. American Statistical Association 100, 577-590 for interpretation and usage of these plots. This function will open a new device as default.
CreateDiagnosticsPlot	Functional Principal Component Analysis Diagnostics plot
CreateFuncBoxPlot	Create functional boxplot using 'bagplot', 'KDE' or 'pointwise' methodology
CreateModeOfVarPlot	Functional Principal Component Analysis: Mode of variation plot
CreateOutliersPlot	Functional Principal Component or Functional Singular Value Decomposition Scores Plot using 'bagplot' or 'KDE' methodology
CreatePathPlot	Create the fitted sample path plot based on the results from FPCA().
CreateScreePlot	Create the scree plot for the fitted eigenvalues
CreateStringingPlot	Create plots for observed and stringed high dimensional data
cumtrapzRcpp	Cumulative Trapezoid Rule Numerical Integration
DynCorr	Dynamical Correlation
Dyn_test	Bootstrap test of Dynamic Correlation
FAM	Functional Additive Models
FCCor	Calculation of functional correlation between two simultaneously observed processes.
FClust	Functional clustering and identifying substructures of longitudinal data
FCReg	Functional Concurrent Regression using 2D smoothing
fdapace	fdapace: Principal Analysis by Conditional Expectation and Applications in Functional Data Analysis (revised version 16 August 2019)
fitted.FPCA	Fitted functional data from FPCA object
fitted.FPCAder	Fitted functional data for derivatives from the FPCAder object
FLM	Functional Linear Models
FLM1	Functional Linear Models New
FOptDes	Optimal Designs for Functional and Longitudinal Data for Trajectory Recovery or Scalar Response Prediction
FPCA	Functional Principal Component Analysis
FPCAder	Obtain the derivatives of eigenfunctions/ eigenfunctions of derivatives (note: these two are not the same)
FPCquantile	Conditional Quantile estimation with functional covariates
FSVD	Functional Singular Value Decomposition
FVPA	Functional Variance Process Analysis for dense functional data
GetCovSurface	Covariance Surface
GetCrCorYX	Create cross-correlation matrix from auto- and cross-covariance matrix
GetCrCorYZ	Create cross-correlation matrix from auto- and cross-covariance matrix
GetCrCovYX	Functional Cross Covariance between longitudinal variable Y and longitudinal variable X
GetCrCovYZ	Functional Cross Covariance between longitudinal variable Y and scalar variable Z
GetMeanCI	Bootstrap pointwise confidence intervals for the mean function for densely observed data.
GetMeanCurve	Mean Curve
GetNormalisedSample	Normalise sparse multivariate functional data
GetNormalizedSample	Normalise sparse multivariate functional data
kCFC	Functional clustering and identifying substructures of longitudinal data using kCFC.
Lwls1D	One dimensional local linear kernel smoother
Lwls2D	Two dimensional local linear kernel smoother.
Lwls2DDeriv	Two dimensional local linear kernel smoother to target derivatives.
MakeBWtoZscore02y	Z-score body-weight for age 0 to 24 months based on WHO standards
MakeFPCAInputs	Format FPCA input
MakeGPFunctionalData	Create a Dense Functional Data sample for a Gaussian process
MakeHCtoZscore02y	Z-score head-circumference for age 0 to 24 months based on WHO standards
MakeLNtoZscore02y	Z-score height for age 0 to 24 months based on WHO standards
MakeSparseGP	Create a sparse Functional Data sample for a Gaussian Process
medfly25	Number of eggs laid daily from medflies
MultiFAM	Functional Additive Models with Multiple Predictor Processes
NormCurvToArea	Normalise a curve to a particular area, by multiplication with a factor
plot.FPCA	Functional Principal Component Analysis Diagnostics plot
predict.FPCA	Predict FPC scores and curves for a new sample given an FPCA object
print.FPCA	Print an FPCA object
print.FSVD	Print an FSVD object
print.WFDA	Print a WFDA object
SBFitting	Iterative Smooth Backfitting Algorithm
SelectK	Selects number of functional principal components for given FPCA output and selection criteria
SetOptions	Set the PCA option list
Sparsify	Sparsify densely observed functional data
str.FPCA	Compactly display the structure of an FPCA object
Stringing	Stringing for High-Dimensional data
trapzRcpp	Trapezoid Rule Numerical Integration
TVAM	Iterative Smooth Backfitting Algorithm
VCAM	Sieve estimation: B-spline based estimation procedure for time-varying additive models. The VCAM function can be used to perform function-to-scalar regression.
WFDA	Time-Warping in Functional Data Analysis: Pairwise curve synchronization for functional data
Wiener	Simulate a standard Wiener processes (Brownian motions)