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Vector-valued functional data in basis representation (f: R -> R^d)

Source: R/tfb-mv.R
tfb_mv.Rd

tfb_mv is the basis-representation analogue of tfd_mv(): it bundles d univariate tfb() vectors (one per output dimension / component) into a single vctrs vector of vector-valued functions \(f: \mathbb{R} \to \mathbb{R}^d\). Each component is fitted independently with the usual univariate tfb() machinery (spline or FPC basis), so all of its arguments (k, bs, penalized, basis, ...) apply per component.

Usage

tfb_mv(data, ...)

# S3 method for class 'tf_mv'
tfb_mv(data, basis = c("spline", "fpc"), ...)

# S3 method for class 'list'
tfb_mv(data, basis = c("spline", "fpc"), arg = NULL, domain = NULL, ...)

# Default S3 method
tfb_mv(data, basis = c("spline", "fpc"), arg = NULL, domain = NULL, ...)

as.tfb_mv(data, ...)

# Default S3 method
as.tfb_mv(data, ...)

Arguments

data

a tfd_mv() / tfb_mv object, a (named) list of univariate tf vectors, or anything tfd_mv() accepts (it is converted to tfd_mv first and then each component is expanded into a basis).

...

forwarded to the univariate tfb() constructor.

basis

spline (default) or fpc basis, see tfb().

arg

evaluation grid for raw (list/matrix/array) inputs, forwarded to tfd_mv().

domain

range of arg, forwarded to tfd_mv().

Value

a tfb_mv object.

Details

By default a single ... is shared across all components (every component gets the same k, bs, sp, etc.). To pass different basis arguments to different components, give the argument as a list named by component names – e.g. tfb_mv(f, k = list(x = 5, y = 12)) fits component x with k = 5 and component y with k = 12. Any list-valued ... whose names do not match the component names is treated as a shared argument value. (Already-tfb components passed via tfb_mv.list() are kept as-is, which is the most permissive way to mix entirely different basis kinds across components.)

See also

Other tf_mv-class: plot.tf_mv(), tf_arclength(), tf_geom, tf_mv_methods, tfb_mfpc(), tfd_mv()

Examples

traj <- tfd_mv(list(x = tf_rgp(5), y = tf_rgp(5)))
tb <- tfb_mv(traj, k = 7, verbose = FALSE)
tb
#> tfb_mv<d=2>[5] (x, y): [0, 1] -> [-2.252416, 1.870235] x [-1.211479, 1.995287]
#> components in basis representation: s(arg, bs = "cr", k = 7, sp = -1)
#> [1]: ███▇▇▆▆▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▆▆▆▆ | ▃▃▂▃▃▄▄▅▆▆▆▆▆▅▅▄▄▄▄▅▆▆▇███
#> [2]: ▇▇███▇▇▆▆▅▄▃▃▃▂▂▃▃▄▅▆▇▇███ | ▅▅▄▃▂▂▁▁▂▂▃▃▄▄▄▅▅▅▄▄▄▄▄▅▅▅
#> [3]: ▄▄▄▄▄▄▄▄▄▅▅▆▆▆▇████▇▇▆▅▄▄▃ | ▃▄▅▅▆▆▇▇▇▆▆▅▅▄▄▄▃▃▃▃▃▄▄▄▄▅
#> [4]: ▁▁▁▁▁▁▁▁▁▂▂▂▂▂▂▂▂▃▃▃▃▄▄▄▄▅ | ▃▂▂▁▁▁▁▁▁▂▃▄▅▆▆▇▇▇▆▆▅▄▃▃▂▂
#> [5]: ▅▅▄▄▄▃▃▃▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▆▆▇ | ▅▅▅▅▅▆▆▆▆▆▆▆▆▆▅▅▄▄▄▅▅▆▆▆▆▆
#> 
tf_ncomp(tb)
#> [1] 2