bifdPar | R Documentation |
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.
bifdPar(bifdobj, Lfdobjs=int2Lfd(2), Lfdobjt=int2Lfd(2), lambdas=0, lambdat=0,
estimate=TRUE)
bifdobj |
a bivariate functional data object. |
Lfdobjs |
either a nonnegative integer or a linear differential operator object for the first argument $s$. If
|
Lfdobjt |
either a nonnegative integer or a linear differential operator object for the first argument $t$. If
|
lambdas |
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. |
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 |
Lfdobjs |
a linear differential operator object (i.e., with class
|
Lfdobjt |
a linear differential operator object (i.e., with class
|
lambdas |
a nonnegative real number |
lambdat |
a nonnegative real number |
estimate |
not currently used |
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
Ramsay, James O., Hooker, Giles, and Graves, Spencer (2009), Functional data analysis with 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.
linmod
#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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