| Decomposition for Amplitude and Phase Variation | AmpPhaseDecomp |
| Arithmatic on functional basis objects | ==.basisfd arithmetic.basisfd |
| Arithmetic on functional data ('fd') objects | *.fd +.fd -.fd arithmetic.fd minus.fd plus.fd times.fd |
| Reshape a vector or array to have 3 dimensions. | as.array3 |
| Convert a spline object to class 'fd' | as.fd as.fd.fdSmooth as.fd.function as.fd.smooth.spline |
| 'as.POXIXct' for number of seconds since the start of 1970. | as.POSIXct1970 |
| Mark Intervals on a Plot Axis | axesIntervals axisIntervals |
| Product of two basisfd objects | *.basisfd basisfd.product |
| Create a bivariate functional data object | bifd |
| Define a Bivariate Functional Parameter Object | bifdPar |
| B-Spline Penalty Matrix | bsplinepen |
| B-spline Basis Function Values | bsplineS |
| Canadian average annual weather cycle | CanadianWeather daily |
| Functional Canonical Correlation Analysis | cca.fd |
| Center Functional Data | center.fd |
| Compare dimensions and dimnames of arrays | checkDim3 checkDims3 |
| Does an argument satisfy required conditions? | checkLogical checkLogicalInteger checkNumeric |
| Extract functional coefficients | coef.fd coef.fdPar coef.fdSmooth coefficients.fd coefficients.fdPar coefficients.fdSmooth |
| Correlation matrix from functional data object(s) | cor.fd |
| Estimate of the covariance surface | covPACE |
| Test if running as CRAN | CRAN |
| Create Basis Set for Functional Data Analysis | create.basis |
| Create a B-spline Basis | create.bspline.basis |
| Create a Constant Basis | create.constant.basis |
| Create an Exponential Basis | create.exponential.basis |
| Create a Fourier Basis | create.fourier.basis |
| Create a Monomial Basis | create.monomial.basis |
| Create a Polygonal Basis | create.polygonal.basis |
| Create a Power Basis Object | create.power.basis |
| Continuously Stirred Tank Reactor | CSTR CSTR2 CSTR2in CSTRfitLS CSTRfn CSTRres CSTRsse |
| Compute a Cumulative Distribution Functional Data Object | cumfd |
| Plot Cycles for a Periodic Bivariate Functional Data Object | cycleplot.fd |
| Create smooth functions that fit scatterplot data. | Data2fd |
| Numeric and character vectors to facilitate working with dates | dateAccessories day.5 dayOfYear dayOfYearShifted daysPerMonth monthAccessories monthBegin.5 monthEnd monthEnd.5 monthLetters monthMid weeks |
| Compute a Probability Density Function | density.fd |
| Compute a Derivative of a Functional Data Object | deriv.fd |
| Degrees of Freedom for Residuals from a Functional Regression | df.residual.fRegress |
| Convert Degrees of Freedom to a Smoothing Parameter Value | df2lambda |
| Get subdirectories | dirs |
| Eigenanalysis preserving dimnames | Eigen |
| Stability Analysis for Principle Differential Analysis | eigen.pda |
| Predicting electricity demand in Adelaide from temperature | ElectricDemand |
| Values of Basis Functions or their Derivatives | eval.basis predict.basisfd |
| Values a Two-argument Functional Data Object | eval.bifd |
| Values of a Functional Data Object | eval.fd fitted.fdSmooth predict.fd predict.fdPar predict.fdSmooth residuals.fdSmooth |
| Values of a Monotone Functional Data Object | eval.monfd fitted.monfd predict.monfd residuals.monfd |
| Evaluate a Basis Penalty Matrix | eval.penalty |
| Evaluate a Positive Functional Data Object | eval.posfd fitted.posfd predict.posfd residuals.posfd |
| Values of a Functional Data Object Defining Surprisal Curves. | eval.surp |
| Evaluate the Diagonal of a Bivariate Functional Data Object | evaldiag.bifd |
| Exponential Basis Function Values | expon |
| Powers of a functional data ('fd') object | exponentiate.fd ^.fd |
| Exponential Penalty Matrix | exponpen |
| Functional Boxplots | boxplot.fd boxplot.fdPar boxplot.fdSmooth fbplot |
| Convert a univariate functional data object to a list | fd2list |
| Functions for statistical analyses of functions | fda |
| Extract plot labels and names for replicates and variables | fdlabels |
| Define a Functional Parameter Object | fdPar |
| Convert 'fd' or 'basisfd' Objects to 'fdPar' Objects | fdParcheck |
| Fourier Basis Function Values | fourier |
| Fourier Penalty Matrix | fourierpen |
| Permutation F-test for functional linear regression. | Fperm.fd |
| Functional Regression Analysis | fRegress fRegress.character fRegress.double fRegress.fd fRegress.formula |
| Computes Cross-validated Error Sum of Integrated Squared Errors for a Functional Regression Model | fRegress.CV |
| Compute Standard errors of Coefficient Functions Estimated by Functional Regression Analysis | fRegress.stderr |
| F-statistic for functional linear regression. | Fstat.fd |
| Hip and knee angle while walking | gait |
| Generalized eigenanalysis | geigen |
| Values of Basis Functions or their Derivatives | getbasismatrix |
| Evaluate a Roughness Penalty Matrix | getbasispenalty |
| Extract the range from a basis object | getbasisrange |
| Berkeley Growth Study data | growth |
| Cursive handwriting samples | handwrit handwritTime |
| Tibia Length for One Baby | infantGrowth |
| Inner products of Functional Data Objects. | inprod |
| Compute Inner Products B-spline Expansions. | inprod.bspline |
| Convert Integer to Linear Differential Operator | int2Lfd |
| Intensity Function for Point Process | intensity.fd |
| Confirm Object is Class "Basisfd" | is.basis |
| Confirm that two objects of class "Basisfd" are identical | is.eqbasis |
| Confirm Object has Class "fd" | is.fd |
| Confirm Object has Class "fdPar" | is.fdPar |
| Confirm Object has Class "fdSmooth" | is.fdSmooth |
| Confirm Object has Class "Lfd" | is.Lfd |
| Extract the knots from a function basis or data object | knots.basisfd knots.fd knots.fdSmooth |
| Convert Smoothing Parameter to Degrees of Freedom | lambda2df |
| Compute GCV Criterion | lambda2gcv |
| Landmark Registration of Functional Observations with Differing Ranges | landmarkreg |
| Define a Linear Differential Operator Object | Lfd |
| Add Lines from Functional Data to a Plot | lines.fd lines.fdSmooth |
| Fit Fully Functional Linear Model | linmod |
| Lip motion | lip lipmarks liptime |
| Search along a line for a minimum within an optimisation algorithm. | lnsrch |
| Plot Columns of Matrices | matplot matplot.Date matplot.default matplot.POSIXct |
| Mean of Functional Data | mean.fd |
| melanoma 1936-1972 | melanoma |
| Evaluate the a monotone function | monfn |
| Evaluate the gradient of a monotone function | mongrad |
| Evaluate the Hessian matrix of a monotone function | monhess |
| Evaluate Monomial Basis | monomial |
| Evaluate Monomial Roughness Penalty Matrix | monomialpen |
| Montreal Daily Temperature | MontrealTemp |
| Nondurable goods index | nondurables |
| Order of a B-spline | norder norder.basisfd norder.bspline norder.default norder.fd |
| Add names to an object | objAndNames |
| Numerical Solution mth Order Differential Equation System | odesolv |
| Functional Principal Components Analysis | pca.fd |
| Estimate the functional principal components | pcaPACE |
| Principal Differential Analysis | pda.fd |
| Stability Analysis for Principle Differential Analysis | pda.overlay |
| Phase-plane plot | phaseplanePlot |
| pinch force data | pinch pinchraw pinchtime |
| Plot a Basis Object | plot.basisfd |
| Plot Functional Canonical Correlation Weight Functions | plot.cca.fd |
| Plot a Functional Data Object | plot.fd plot.fdPar plot.fdSmooth |
| Plot a Linear Differential Operator Object | plot.Lfd |
| Plot Functional Principal Components | plot.pca.fd |
| Plot Principle Differential Analysis Components | plot.pda.fd |
| Plot a functional parameter object with confidence limits | plotbeta |
| Plot a Functional Data Object With Data | plotfit.fd plotfit.fdSmooth |
| Plot Principal Component Scores | plotscores |
| Polynomial extrapolation for a converging sequence of one or more values | polintmat |
| Polygonal Basis Function Values | polyg |
| Polygonal Penalty Matrix | polygpen |
| Power Basis Function Values | powerbasis |
| Power Penalty Matrix | powerpen |
| Convert a B-spline function to piece-wise polynomial form | ppBspline |
| Predict method for Functional Regression | predict.fRegress |
| Approximate Functional Data Using a Basis | project.basis |
| Quadrature points and weights for Simpson's rule | quadset |
| Reconstruct data curves using functional principal components | reconsCurves |
| Reflux and tray level in a refinery | refinery |
| Regina Daily Precipitation | ReginaPrecip |
| Register Functional Data Objects Using a Continuous Criterion | register.fd |
| Register Functional Data Objects with Pre-Computed Warping Functions | register.newfd |
| Estimates of functional Principal Component scores through PACE | scoresPACE |
| Standard Deviation of Functional Data | sd.fd std.fd stddev.fd stdev.fd |
| Sea Bird Counts | seabird |
| Construct a functional data object by smoothing data using a roughness penalty | smooth.basis smooth.basis1 smooth.basis2 smooth.basis3 |
| Construct a functional data object by smoothing data using a roughness penalty | smooth.basis.sparse |
| Smooth Data Using a Directly Specified Roughness Penalty | smooth.basisPar |
| Smooth a discrete surface over a rectangular lattice | smooth.bibasis |
| Smooth a Functional Data Object Using an Indirectly Specified Roughness Penalty | smooth.fd |
| Smooth a functional data object using a directly specified roughness penalty | smooth.fdPar |
| Monotone Smoothing of Data | smooth.monotone |
| Estimates a Smooth Warping Function Mapping an Interval into Another | smooth.morph |
| Smooth Data with a Positive Function | smooth.pos |
| Smooth the mean function of sparse data | smooth.sparse.mean |
| Fit data with surprisal smoothing. | smooth.surp |
| Creates a list of sparse data from a matrix | sparse.list |
| Creates a matrix of sparse data with NAs out of a list | sparse.mat |
| Check a step size value for being within parameter limits. | stepchk |
| Compute a new step size for a linear search within an optimization algorithm. | stepit |
| Sum of Functional Data | sum.fd |
| Summarize a Functional Data Object | summary.basisfd |
| Summarize a Bivariate Functional Data Object | summary.bifd |
| Summarize a Functional Data Object | summary.fd |
| Summarize a Functional Parameter Object | summary.fdPar |
| Summarize a Linear Differential Operator Object | summary.Lfd |
| Evaluate the fit of surprisal curves to binned psychometric data. | surp.fit |
| solve(A, B) where A is symmetric | symsolve |
| Permutation t-test for two groups of functional data objects. | tperm.fd |
| Approximate the functional inner product of two functional data objects using the trapezpoidal rule over a fine mesh of value. | trapzmat |
| Variance, Covariance, and Correlation Surfaces for Functional Data Object(s) | var.fd |
| Rotate a Matrix of Component Loadings using the VARIMAX Criterion | varmx |
| Rotation of Functional Canonical Components with VARIMAX | varmx.cca.fd |
| Rotation of Functional Principal Components with VARIMAX Criterion | varmx.pca.fd |
| Make a Linear Differential Operator Object from a Vector | vec2Lfd |
| Check a vector of weights | wtcheck |
| Check Data Arrays for Smoothing Functions | ycheck |
| Orthonormal Matrix with Columns Summing to Zero | zerobasis |
| Does the range of the input contain 0? | zerofind |