fdaACF (version 0.1.0)

estimate_iid_distr_Imhof: Estimate distribution of the fACF under the iid. hypothesis using Imhof's method

Description

Estimate the distribution of the autocorrelation function under the hypothesis of strong functional white noise. This function uses Imhof's method to estimate the distribution.

Usage

estimate_iid_distr_Imhof(Y, v, autocovSurface, matindex, figure = FALSE, ...)

Arguments

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.

v

Discretization points of the curves, by default seq(from = 0, to = 1, length.out = 100).

autocovSurface

An \((m x m)\) matrix with the discretized values of the autocovariance operator \(\hat{C}_{0}\), obtained by calling the function obtain_autocovariance. The value \(m\) indicates the number of points observed in each curve.

matindex

A vector containing the L2 norm of the autocovariance function. It can be obtained by calling function obtain_suface_L2_norm.

figure

Logical. If TRUE, plots the estimated distribution.

...

Further arguments passed to the plot function.

Value

Return a list with:

• ex: Knots where the distribution has been estimated

• ef: Discretized values of the estimated distribution.

Examples

# NOT RUN {
# Example 1

N <- 100
v <- seq(from = 0, to = 1, length.out = 10)
sig <- 2
Y <- simulate_iid_brownian_bridge(N, v, sig)
nlags <- 1
autocovSurface <- obtain_autocovariance(Y,nlags)
matindex <- obtain_suface_L2_norm (v,autocovSurface)
# Remove lag 0
matindex <- matindex[-1]
Imhof_dist <- estimate_iid_distr_Imhof(Y,v,autocovSurface,matindex)
plot(Imhof_dist$ex,Imhof_dist$ef,type = "l",main = "ecdf obtained by Imhof's method")
grid()

# }
# NOT RUN {
# Example 2

N <- 400
v <- seq(from = 0, to = 1, length.out = 50)
sig <- 2
Y <- simulate_iid_brownian_bridge(N, v, sig)
autocovSurface <- obtain_autocovariance(Y,nlags)
matindex <- obtain_suface_L2_norm (v,autocovSurface)
# Remove lag 0
matindex <- matindex[-1]
Imhof_dist <- estimate_iid_distr_Imhof(Y,v,autocovSurface,matindex)
plot(Imhof_dist$ex,Imhof_dist$ef,type = "l",main = "ecdf obtained by Imhof's method")
grid()
# }