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.
a nonnegative real number specifying the amount of smoothing
to be applied to the estimated functional parameter $x(s,t)$
as a function of $s$..
lambdat
a nonnegative real number specifying the amount of smoothing
to be applied to the estimated functional parameter $x(s,t)$
as a function of $t$..
estimate
not currently used.
Value
a bivariate functional parameter object (i.e., an object of class bifdPar),
which is a list with the following components:
bifd
a functional data object (i.e., with class bifd)
Lfdobjs
a linear differential operator object (i.e., with class
Lfdobjs)
Lfdobjt
a linear differential operator object (i.e., with class
Lfdobjt)
lambdas
a nonnegative real number
lambdat
a nonnegative real number
estimate
not currently used
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
#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.