| 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 |
| 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 |
| 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 |
| 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. |
| Lwls2Dv1 | Two dimensional local linear kernel smoother. |
| 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 |
| medfly25 | Number of eggs laid daily from medflies |
| oldFCReg | Functional Principal Component Analysis Concurrent Regression with Functional dependent variable |
| 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 |
| Wiener | Simulate standard Wiener processes (Brownian motions) |