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fda (version 2.4.0)

bifdPar: Define a Bivariate Functional Parameter Object

Description

Functional parameter objects are used as arguments to functions that estimate functional parameters, such as smoothing functions like smooth.basis. A bivariate functional parameter object supplies the analogous information required for smoothing bivariate data using a bivariate functional data object $x(s,t)$. The arguments are the same as those for fdPar objects, except that two linear differential operator objects and two smoothing parameters must be applied, each pair corresponding to one of the arguments $s$ and $t$ of the bivariate functional data object.

Usage

bifdPar(bifdobj, Lfdobjs=int2Lfd(2), Lfdobjt=int2Lfd(2), lambdas=0, lambdat=0,
      estimate=TRUE)

Arguments

bifdobj
a bivariate functional data object.
Lfdobjs
either a nonnegative integer or a linear differential operator object for the first argument $s$. If NULL, Lfdobjs depends on bifdobj[['sbasis']][['type']]:
  • bspline
{ Lfdobjs <- int2Lfd(max(0, norder-2)),

Value

  • a bivariate functional parameter object (i.e., an object of class bifdPar), which is a list with the following components:
  • bifda functional data object (i.e., with class bifd)
  • Lfdobjsa linear differential operator object (i.e., with class Lfdobjs)
  • Lfdobjta linear differential operator object (i.e., with class Lfdobjt)
  • lambdasa nonnegative real number
  • lambdata nonnegative real number
  • estimatenot currently used

item

  • Lfdobjt
  • fourier
  • anything else
  • lambdas
  • lambdat
  • estimate

code

Lfdobj <- vec2Lfd(c(0,(2*pi/diff(rngt))^2,0), rngt)

itemize

  • bspline

source

Ramsay, James O., Hooker, Giles, and Graves, Spencer (2009) Functional Data Analysis in R and Matlab, Springer, New York. Ramsay, James O., and Silverman, Bernard W. (2005), Functional Data Analysis, 2nd ed., Springer, New York. Ramsay, James O., and Silverman, Bernard W. (2002), Applied Functional Data Analysis, Springer, New York

See Also

linmod

Examples

Run this code
#See the prediction of precipitation using temperature as
#the independent variable in the analysis of the daily weather
#data, and the analysis of the Swedish mortality data.

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