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  "Title": "Functional Data Analysis",
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  "Description": "These functions were developed to support functional data\nanalysis as described in Ramsay, J. O. and Silverman, B. W.\n(2005) Functional Data Analysis. New York: Springer and in\nRamsay, J. O., Hooker, Giles, and Graves, Spencer (2009).\nFunctional Data Analysis with R and Matlab (Springer). The\npackage includes data sets and script files working many\nexamples including all but one of the 76 figures in this latter\nbook.  Matlab versions are available by ftp from\n<https://www.psych.mcgill.ca/misc/fda/downloads/FDAfuns/>.",
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      "page": "arithmetic.basisfd",
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      "page": "center.fd",
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      "page": "checkLogicalInteger",
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        "checkNumeric"
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      "page": "coef",
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      "page": "create.power.basis",
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      "page": "CSTR",
      "title": "Continuously Stirred Tank Reactor",
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        "CSTR2in",
        "CSTRfitLS",
        "CSTRfn",
        "CSTRres",
        "CSTRsse"
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      "page": "cumfd",
      "title": "Compute a Cumulative Distribution Functional Data Object",
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      "page": "cycleplot.fd",
      "title": "Plot Cycles for a Periodic Bivariate Functional Data Object",
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      "page": "Data2fd",
      "title": "Create smooth functions that fit scatterplot data.",
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      "page": "dateAccessories",
      "title": "Numeric and character vectors to facilitate working with dates",
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        "day.5",
        "dayOfYear",
        "dayOfYearShifted",
        "daysPerMonth",
        "monthAccessories",
        "monthBegin.5",
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        "monthEnd.5",
        "monthLetters",
        "monthMid",
        "weeks"
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    {
      "page": "density.fd",
      "title": "Compute a Probability Density Function",
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    {
      "page": "deriv.fd",
      "title": "Compute a Derivative of a Functional Data Object",
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      "page": "df.residual.fRegress",
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      "page": "df2lambda",
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    {
      "page": "dirs",
      "title": "Get subdirectories",
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    {
      "page": "Eigen",
      "title": "Eigenanalysis preserving dimnames",
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      "page": "eigen.pda",
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      "page": "ElectricDemand",
      "title": "Predicting electricity demand in Adelaide from temperature",
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      "page": "eval.basis",
      "title": "Values of Basis Functions or their Derivatives",
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      "page": "eval.bifd",
      "title": "Values a Two-argument Functional Data Object",
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      "page": "eval.fd",
      "title": "Values of a Functional Data Object",
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        "predict.fdPar",
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      "page": "eval.monfd",
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        "residuals.monfd"
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      "page": "eval.penalty",
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    {
      "page": "eval.posfd",
      "title": "Evaluate a Positive Functional Data Object",
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        "residuals.posfd"
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      "page": "eval.surp",
      "title": "Values of a Functional Data Object Defining Surprisal Curves.",
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      "page": "evaldiag.bifd",
      "title": "Evaluate the Diagonal of a Bivariate Functional Data Object",
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      "page": "expon",
      "title": "Exponential Basis Function Values",
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    {
      "page": "exponentiate.fd",
      "title": "Powers of a functional data ('fd') object",
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        "^.fd"
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      "page": "exponpen",
      "title": "Exponential Penalty Matrix",
      "topics": [
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    {
      "page": "fbplot",
      "title": "Functional Boxplots",
      "topics": [
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        "boxplot.fdPar",
        "boxplot.fdSmooth",
        "fbplot"
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    {
      "page": "fd2list",
      "title": "Convert a univariate functional data object to a list",
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    {
      "page": "fda-package",
      "title": "Functions for statistical analyses of functions",
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        "fda"
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    {
      "page": "fdlabels",
      "title": "Extract plot labels and names for replicates and variables",
      "topics": [
        "fdlabels"
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    {
      "page": "fdPar",
      "title": "Define a Functional Parameter Object",
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    {
      "page": "fdParcheck",
      "title": "Convert 'fd' or 'basisfd' Objects to 'fdPar' Objects",
      "topics": [
        "fdParcheck"
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    {
      "page": "fourier",
      "title": "Fourier Basis Function Values",
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    {
      "page": "fourierpen",
      "title": "Fourier Penalty Matrix",
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    {
      "page": "Fperm.fd",
      "title": "Permutation F-test for functional linear regression.",
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      "page": "fRegress",
      "title": "Functional Regression Analysis",
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        "fRegress.character",
        "fRegress.double",
        "fRegress.fd",
        "fRegress.formula"
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    {
      "page": "fRegress.CV",
      "title": "Computes Cross-validated Error Sum of Integrated Squared Errors for a Functional Regression Model",
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    {
      "page": "fRegress.stderr",
      "title": "Compute Standard errors of Coefficient Functions Estimated by Functional Regression Analysis",
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      "page": "Fstat.fd",
      "title": "F-statistic for functional linear regression.",
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      "page": "gait",
      "title": "Hip and knee angle while walking",
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        "gait"
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      "page": "geigen",
      "title": "Generalized eigenanalysis",
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    {
      "page": "getbasismatrix",
      "title": "Values of Basis Functions or their Derivatives",
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    {
      "page": "getbasispenalty",
      "title": "Evaluate a Roughness Penalty Matrix",
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    {
      "page": "getbasisrange",
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    {
      "page": "growth",
      "title": "Berkeley Growth Study data",
      "topics": [
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    },
    {
      "page": "handwrit",
      "title": "Cursive handwriting samples",
      "topics": [
        "handwrit",
        "handwritTime"
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    },
    {
      "page": "infantGrowth",
      "title": "Tibia Length for One Baby",
      "topics": [
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    },
    {
      "page": "inprod",
      "title": "Inner products of Functional Data Objects.",
      "topics": [
        "inprod"
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    },
    {
      "page": "inprod.Bspline",
      "title": "Compute Inner Products B-spline Expansions.",
      "topics": [
        "inprod.bspline"
      ]
    },
    {
      "page": "int2Lfd",
      "title": "Convert Integer to Linear Differential Operator",
      "topics": [
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