odesolv: Numerical Solution mth Order Differential Equation System

In fda: Functional Data Analysis

Numerical Solution mth Order Differential Equation System

Description

The system of differential equations is linear, with possibly time-varying coefficient functions. The numerical solution is computed with the Runge-Kutta method.

Usage

odesolv(bwtlist, ystart=diag(rep(1,norder)),
        h0=width/100, hmin=width*1e-10, hmax=width*0.5,
        EPS=1e-4, MAXSTP=1000)

Arguments

bwtlist	a list whose members are functional parameter objects defining the weight functions for the linear differential equation.
ystart	a vector of initial values for the equations. These are the values at time 0 of the solution and its first m - 1 derivatives.
h0	a positive initial step size.
hmin	the minimum allowable step size.
hmax	the maximum allowable step size.
EPS	a convergence criterion.
MAXSTP	the maximum number of steps allowed.

Details

This function is required to compute a set of solutions of an estimated linear differential equation in order compute a fit to the data that solves the equation. Such a fit will be a linear combinations of m independent solutions.

Value

a named list of length 2 containing

tp	a vector of time values at which the system is evaluated
yp	a matrix of variable values corresponding to tp.

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

pda.fd. For new applications, users are encouraged to consider deSolve. The deSolve package provides general solvers for ordinary and partial differential equations, as well as differential algebraic equations and delay differential equations.

Examples

#See the analyses of the lip data.

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