obtain_autocov_eigenvalues: Estimate eigenvalues of the autocovariance function

In fdaACF: Autocorrelation Function for Functional Time Series

Description

Estimate the eigenvalues of the sample autocovariance function \hat{C}_{0}. This functions returns the eigenvalues which are greater than the value epsilon.

Usage

obtain_autocov_eigenvalues(v, Y, epsilon = 1e-04)

Arguments

v	Discretization points of the curves, by default seq(from = 0, to = 1, length.out = 100).
Y	Matrix containing the discretized values of the functional time series. The dimension of the matrix is (n x m), where n is the number of curves and m is the number of points observed in each curve.
epsilon	Value used to determine how many eigenvalues will be returned. The eigenvalues λ_{j}/λ_{1} > \code{epsilon} will be returned. By default epsilon = 0.0001.

Value

A vector containing the k eigenvalues greater than epsilon.

Examples

N <- 100
v <- seq(from = 0, to = 1, length.out = 10)
sig <- 2
Y <- simulate_iid_brownian_bridge(N, v, sig)
lambda <- obtain_autocov_eigenvalues(v = v, Y = Y)

fdaACF documentation built on Oct. 23, 2020, 8:05 p.m.