evaldiag.bifd: Evaluate the Diagonal of a Bivariate Functional Data Object

In fda: Functional Data Analysis

Evaluate the Diagonal of a Bivariate Functional Data Object

Description

Bivariate function data objects are functions of two arguments, $f(s,t)$. It can be useful to evaluate the function for argument values satisfying $s=t$, such as evaluating the univariate variance function given the bivariate function that defines the variance-covariance function or surface. A linear differential operator can be applied to function $f(s,t)$ considered as a univariate function of either object holding the other object fixed.

Usage

evaldiag.bifd(evalarg, bifdobj, sLfd=int2Lfd(0), tLfd=int2Lfd(0))

Arguments

evalarg	a vector of values of $s = t$.
bifdobj	a bivariate functional data object of the bifd class.
sLfd	either a nonnegative integer or a linear differential operator object.
tLfd	either a nonnegative integer or a linear differential operator object.

Value

a vector or matrix of diagonal function values.

References

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.

See Also

var.fd, eval.bifd

fda documentation built on Sept. 30, 2024, 9:19 a.m.