estimate_iid_distr_Imhof {fdaACF} | R Documentation |
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 |
v |
Discretization points of the curves, by default
|
autocovSurface |
An |
matindex |
A vector containing the L2 norm of
the autocovariance function. It can be obtained by calling
function |
figure |
Logical. If |
... |
Further arguments passed to the |
Value
Return a list with:
-
ex
: Knots where the distribution has been estimated -
ef
: Discretized values of the estimated distribution.
Examples
# 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()
# 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()