Function reference
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tfd()as.tfd()as.tfd_irreg() - Constructors for vectors of "raw" functional data
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tfb()tfb_wavelet()as.tfb() - Constructors for functional data in basis representation
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as.data.frame(<tf>)as.matrix(<tf>)as.function(<tf>) - Convert functional data back to tabular data formats
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tfb_spline() - Spline-based representation of functional data
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tfb_fpc() - Functional data in FPC-basis representation
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fpc_wsvd() - Eigenfunctions via weighted, regularized SVD
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tf_rebase() - Change (basis) representation of a
tf-object
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`[`(<tf>)`[<-`(<tf>) - Accessing, evaluating, subsetting and subassigning
tfvectors
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tf_approx_linear()tf_approx_spline()tf_approx_none()tf_approx_fill_extend()tf_approx_locf()tf_approx_nocb() - Inter- and extrapolation functions for
tfd-objects
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tf_evaluate() - Evaluate
tf-vectors for given argument values
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tf_interpolate() - Re-evaluate
tf-objects on a new grid of argument values.
Arithmetic, logical and summary functions
Functionality for computing with and comparing functional data
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Ops(<tf>)`==`(<tfd>)`!=`(<tfd>)`==`(<tfb>)`!=`(<tfb>)Ops(<tfd>)Ops(<tfb>)Math(<tfd>)Math(<tfb>)Summary(<tf>)cummax(<tfd>)cummin(<tfd>)cumsum(<tfd>)cumprod(<tfd>)cummax(<tfb>)cummin(<tfb>)cumsum(<tfb>)cumprod(<tfb>) - Math, Summary and Ops Methods for
tf
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mean(<tf>)median(<tf>)sd()var()summary(<tf>) - Functions that summarize
tfobjects across argument values
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tf_fwise()tf_fmax()tf_fmin()tf_fmedian()tf_frange()tf_fmean()tf_fvar()tf_fsd()tf_crosscov()tf_crosscor() - Summarize each
tfin a vector
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tf_depth() - Functional Data Depth
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tf_derive() - Differentiating functional data: approximating derivative functions
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tf_integrate() - Integrals and anti-derivatives of functional data
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tf_smooth() - Simple smoothing of
tfobjects
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plot(<tf>)lines(<tf>)points(<tf>) baseplots fortfs
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print(<tf>)print(<tfd_reg>)print(<tfd_irreg>)print(<tfb>)format(<tf>) - Pretty printing and formatting for functional data
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prep_plotting_arg() - Preprocess evaluation grid for plotting
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tf_where()tf_anywhere() - Find out where functional data fulfills certain conditions.
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tf_zoom() - Functions to zoom in/out on functions
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tf_arg()tf_evaluations()tf_count()tf_domain()`tf_domain<-`()tf_evaluator()`tf_evaluator<-`()tf_basis()`tf_arg<-`()coef(<tfb>)rev(<tf>)is.na(<tf>)is.na(<tfd_irreg>)is_tf()is_tfd()is_reg()is_tfd_reg()is_irreg()is_tfd_irreg()is_tfb()is_tfb_spline()is_tfb_fpc() - Utility functions for
tf-objects
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tf_rgp() - Gaussian Process random generator
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tf_jiggle()tf_sparsify() - Make a
tf(more) irregular
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in_range()`%inr%` - Find out if values are inside given bounds
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ensure_list() - Turns any object into a list
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unique_id() - Make syntactically valid unique names
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vec_cast(<tfd_reg>)vec_cast(<tfd_irreg>)vec_cast.tfd_reg(<tfd_reg>)vec_cast.tfd_reg(<tfd_irreg>)vec_cast.tfd_reg(<tfb_spline>)vec_cast.tfd_reg(<tfb_fpc>)vec_cast.tfd_irreg(<tfd_reg>)vec_cast.tfd_irreg(<tfd_irreg>)vec_cast.tfd_irreg(<tfb_spline>)vec_cast.tfd_irreg(<tfb_fpc>)vec_cast(<tfb_spline>)vec_cast(<tfb_fpc>)vec_cast.tfb_spline(<tfb_spline>)vec_cast.tfb_spline(<tfb_fpc>)vec_cast.tfb_fpc(<tfb_spline>)vec_cast.tfb_fpc(<tfb_fpc>)vec_cast.tfb_spline(<tfd_reg>)vec_cast.tfb_spline(<tfd_irreg>)vec_cast.tfb_fpc(<tfd_reg>)vec_cast.tfb_fpc(<tfd_irreg>)vec_ptype2(<tfd_reg>)vec_ptype2.tfd_reg(<tfd_reg>)vec_ptype2.tfd_reg(<tfd_irreg>)vec_ptype2.tfd_reg(<tfb_spline>)vec_ptype2.tfd_reg(<tfb_fpc>)vec_ptype2(<tfd_irreg>)vec_ptype2.tfd_irreg(<tfd_reg>)vec_ptype2.tfd_irreg(<tfd_irreg>)vec_ptype2.tfd_irreg(<tfb_spline>)vec_ptype2.tfd_irreg(<tfb_fpc>)vec_ptype2(<tfb_spline>)vec_ptype2.tfb_spline(<tfb_spline>)vec_ptype2.tfb_spline(<tfb_fpc>)vec_ptype2.tfb_spline(<tfd_reg>)vec_ptype2.tfb_spline(<tfd_irreg>)vec_ptype2(<tfb_fpc>)vec_ptype2.tfb_fpc(<tfb_spline>)vec_ptype2.tfb_fpc(<tfb_fpc>)vec_ptype2.tfb_fpc(<tfd_reg>)vec_ptype2.tfb_fpc(<tfd_irreg>) vctrsmethods fortfobjects
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tftf-package - tf: S3 Classes and Methods for Tidy Functional Data