dgp.fiid: Data Generating Process - Independent Process
In yzhao7322/CurVol: Curve Data Volatility Analysis

Description Usage Arguments Details Value See Also Examples

dgp.fiid function generates iid functional curve data following the Ornstein–Uhlenbeck process.

1	dgp.fiid(grid_point, N)

`grid_point`	The number of grid point in each curve observation.
`N`	The sample size.

x_i(t)=e^{-t/2}W_i(e^t), t \in [0,1],
where W_i(t) is a standard Brownian Motion.

A (grid_point) x (number of observations) matrix for iid sequences, where the finite realization of curves are stored in columns.

dgp.fgarch

# generate discrete evaluations of 100 iid curves that each curve is realized on 50 grid points.
yd_iid = dgp.fiid(50, 100)

# smooth discrete data into functional curves.
fd = fda::Data2fd(argvals=seq(0,1,len = 50),y=yd_iid,fda::create.bspline.basis(nbasis = 32))