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| bsplinepen | B-Spline Penalty Matrix |
| bsplineS | B-spline Basis Function Values |
| cca.fd | Functional Canonical Correlation Analysis |
| center.fd | Center Functional Data |
| create.bspline.basis | Create a B-spline Basis |
| create.constant.basis | Create a Constant Basis |
| create.exponential.basis | Create an Exponential Basis |
| create.fourier.basis | Create a Fourier Basis |
| create.monomial.basis | Create a Monomial Basis |
| create.polygonal.basis | Create a Polygonal Basis |
| create.polynomial.basis | Create a Polynomial Basis |
| create.power.basis | Create a Power Basis Object |
| cycleplot.fd | Plot Cycles for a Periodic Bivariate Functional Data Object |
| data2fd | Convert Discrete Data to Functional Data |
| density.fd | Compute a Probability Density Function |
| deriv.fd | Compute a Derivative of a Functional Data Object |
| df2lambda | Convert Degrees of Freedom to a Smoothing Parameter Value |
| eval.basis | Values of Basis Functions or their Derivatives |
| eval.bifd | Values a Two-argument Functional Data Object |
| eval.fd | Values of a Functional Data Object |
| eval.monfd | Values of a Monotone Functional Data Object |
| eval.penalty | Evaluate a Basis Penalty Matrix |
| eval.posfd | Evaluate a Positive Functional Data Object |
| evaldiag.bifd | Evaluate the Diagonal of a Bivariate Functional Data Object |
| expon | Exponential Basis Function Values |
| exponpen | Exponential Penalty Matrix |
| fdPar | Define a Functional Parameter Object |
| fourier | Fourier Basis Function Values |
| fourierpen | Fourier Penalty Matrix |
| fRegress | A Functional Regression Analysis of the Concurrent Type |
| fRegress.CV | Computes Cross-validated Error Sum of Squares for a Functional Regression Model |
| fRegress.stderr | Compute Standard errors of Coefficient Functions Estimated by Functional Regression Analysis |
| getbasismatrix | Values of Basis Functions or their Derivatives |
| getbasispenalty | Evaluate a Roughness Penalty Matrix |
| inprod | Inner products of Functional Data Objects. |
| inprod.bspline | Compute Inner Products B-spline Expansions. |
| int2Lfd | Convert Integer to Linear Differential Operator |
| intensity.fd | Intensity Function for Point Process |
| is.basis | Confirm Object is Class "Basisfd" |
| is.fd | Confirm Object has Class "fd" |
| is.fdPar | Confirm Object has Class "fdPar" |
| is.Lfd | Confirm Object has Class "Lfd" |
| lambda2df | Convert Smoothing Parameter to Degrees of Freedom |
| lambda2gcv | Compute GCV Criterion |
| landmarkreg | Landmark Registration of Functional Observations |
| Lfd | Define a Linear Differential Operator Object |
| lines.fd | Add Lines from Functional Data to a Plot |
| linmod | Fit Fully Functional Linear Model |
| mean.fd | Mean of Functional Data |
| monomial | Evaluate Monomial Basis |
| monomialpen | Evaluate Monomial Roughness Penalty Matrix |
| odesolv | Numerical Solution mth Order Differential Equation System |
| pca.fd | Functional Principal Components Analysis |
| pda.fd | Principal Differential Analysis |
| plot.basisfd | Plot a Basis Object |
| plot.fd | Plot a Functional Data Object |
| plotfit.fd | Plot a Functional Data Object With Data |
| plotscores | Plot Principal Component Scores |
| polyg | Polygonal Basis Function Values |
| polygpen | Polygonal Penalty Matrix |
| powerbasis | Power Basis Function Values |
| powerpen | Power Penalty Matrix |
| project.basis | Approximate Functional Data Using a Basis |
| register.fd | Register Functional Data Objects Using a Continuous Criterion |
| smooth.basis | Smooth Data with a Roughness Penalty |
| smooth.fd | Smooth a Functional Data Object Using a Roughness Penalty |
| smooth.monotone | Monotone Smoothing of Data |
| smooth.morph | Estimates a Smooth Warping Function |
| smooth.pos | Smooth Data with a Positive Function |
| std.fd | Standard Deviation of Functional Data |
| stddev.fd | Standard Deviation of Functional Data |
| sum.fd | Sum of Functional Data |
| summary.bifd | Summarize a Bivariate Functional Data Object |
| summary.fd | Summarize a Functional Data Object |
| summary.fdPar | Summarize a Functional Parameter Object |
| summary.Lfd | Summarize a Linear Differential Operator Object |
| var.fd | Variance and Covariance Surfaces for a Functional Data Object |
| varmx | Rotate a Matrix of Component Loadings using the VARIMAX Criterion |
| varmx.cca.fd | Rotation of Functional Canonical Components with VARIMAX |
| varmx.pca.fd | Rotation of Functional Principal Components with VARIMAX Criterion |
| vec2Lfd | Make a Linear Differential Operator Object from a Vector |