Function reference
-
tfd()
as.tfd()
as.tfd_irreg()
- Constructors for vectors of "raw" functional data
-
tfb()
tfb_wavelet()
as.tfb()
- Constructors for functional data in basis representation
-
as.data.frame(<tf>)
as.matrix(<tf>)
as.function(<tf>)
- Convert functional data back to tabular data formats
-
tfb_spline()
- Spline-based representation of functional data
-
tfb_fpc()
- Functional data in FPC-basis representation
-
fpc_wsvd()
- Eigenfunctions via weighted, regularized SVD
-
tf_rebase()
- Change (basis) representation of a
tf
-object
-
`[`(<tf>)
`[<-`(<tf>)
- Accessing, evaluating, subsetting and subassigning
tf
vectors
-
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
-
tf_evaluate()
- Evaluate
tf
-vectors for given argument values
-
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
-
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
-
mean(<tf>)
median(<tf>)
sd()
var()
summary(<tf>)
- Functions that summarize
tf
objects across argument values
-
tf_fwise()
tf_fmax()
tf_fmin()
tf_fmedian()
tf_frange()
tf_fmean()
tf_fvar()
tf_fsd()
tf_crosscov()
tf_crosscor()
- Summarize each
tf
in a vector
-
tf_depth()
- Functional Data Depth
-
tf_derive()
- Differentiating functional data: approximating derivative functions
-
tf_integrate()
- Integrals and anti-derivatives of functional data
-
tf_smooth()
- Simple smoothing of
tf
objects
-
plot(<tf>)
lines(<tf>)
points(<tf>)
base
plots fortf
s
-
print(<tf>)
print(<tfd_reg>)
print(<tfd_irreg>)
print(<tfb>)
format(<tf>)
- Pretty printing and formatting for functional data
-
prep_plotting_arg()
- Preprocess evaluation grid for plotting
-
tf_where()
tf_anywhere()
- Find out where functional data fulfills certain conditions.
-
tf_zoom()
- Functions to zoom in/out on functions
-
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
-
tf_rgp()
- Gaussian Process random generator
-
tf_jiggle()
tf_sparsify()
- Make a
tf
(more) irregular
-
in_range()
`%inr%`
- Find out if values are inside given bounds
-
ensure_list()
- Turns any object into a list
-
unique_id()
- Make syntactically valid unique names
-
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>)
vctrs
methods fortf
objects
-
tf
tf-package
- tf: S3 Classes and Methods for Tidy Functional Data