Functional Data Analysis and Empirical Dynamics


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Documentation for package ‘fdapace’ version 0.3.0

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fdapace-package PACE: Principal Analysis by Conditional Expectation
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
CreateBWPlot Functional Principal Component Analysis Bandwidth Diagnostics plot
CreateCovPlot Create the covariance surface plot based on the results from FPCA() or FPCder().
CreateDesignPlot Create the design plot of the functional data.
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
FCCor Calculate functional correlation between two simultaneously observed processes.
FClust Functional clustering and identifying substructures of longitudinal data
FCReg Functional Concurrent Regression by 2D smoothing method.
fdapace PACE: Principal Analysis by Conditional Expectation
fitted.FPCA Fitted functional sample from FPCA object
fitted.FPCAder Fitted functional sample from FPCAder object
FOptDes Optimal Designs for Functional and Longitudinal Data for Trajectory Recovery or Scalar Response Prediction
FPCA Functional Principal Component Analysis
FPCAder Take derivative of an FPCA object
FSVD Functional Singular Value Decomposition
FVPA Functional Variance Process Analysis for dense functional data
GetCrCorYX Make cross-correlation matrix from auto- and cross-covariance matrix
GetCrCorYZ Make 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
GetNormalisedSample Normalise sparse functional sample
GetNormalizedSample Normalise sparse functional sample
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 with derivatives.
MakeBWtoZscore02y Z-score body-weight for age 0 to 24 months based on WHO standards
MakeFPCAInputs Format FPCA input
MakeGPFunctionalData Make Gaussian Process Dense Functional Data sample
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 Make Gaussian Process Sparse Functional Data sample
medfly25 Number of eggs laid daily from medflies
plot.FPCA Functional Principal Component Analysis Diagnostics plot
print.FPCA Print an FPCA object
print.FSVD Print an FSVD object
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
WFDA Warped Functional DAta Analysis
Wiener Simulate standard Wiener processes (Brownian motions)