compositionalSpline: Compositional spline

Description Usage Arguments Details Value Author(s) References

View source: R/CompositionalSpline.R

Description

This code implements the compositional smoothing splines grounded on the theory of Bayes spaces.

Usage

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compositionalSpline(
  t,
  clrf,
  knots,
  w,
  order,
  der,
  alpha,
  spline.plot = FALSE,
  basis.plot = FALSE
)

Arguments

t

class midpoints

clrf

clr transformed values at class midpoints, i.e., fcenLR(f(t))

knots

sequence of knots

w

weights

order

order of the spline (i.e., degree + 1)

der

lth derivation

alpha

smoothing parameter

spline.plot

if TRUE, the resulting spline is plotted

basis.plot

if TRUE, the ZB-spline basis system is plotted

Details

The compositional splines enable to construct a spline basis in the centred logratio (clr) space of density functions (ZB-spline basis) and consequently also in the original space of densities (CB-spline basis).The resulting compositional splines in the clr space as well as the ZB-spline basis satisfy the zero integral constraint. This enables to work with compositional splines consistently in the framework of the Bayes space methodology.

Augmented knot sequence is obtained from the original knots by adding #(order-1) multiple endpoints.

Value

J

value of the functional J

ZB_coef

ZB-spline basis coeffcients

CV

score of cross-validation

GCV

score of generalized cross-validation

Author(s)

J. Machalova jitka.machalova@upol.cz, R. Talska talskarenata@seznam.cz

References

Machalova, J., Talska, R., Hron, K. Gaba, A. Compositional splines for representation of density functions. Comput Stat (2020). https://doi.org/10.1007/s00180-020-01042-7


robCompositions documentation built on Jan. 13, 2021, 10:07 p.m.