Description Usage Arguments Value Examples
View source: R/estimate_distribution.R
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.
1 2 | estimate_iid_distr_Imhof(Y, v, autocovSurface, matindex, figure = FALSE,
...)
|
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
|
autocovSurface |
An (m x m) matrix with the discretized
values of the autocovariance operator \hat{C}_{0}, obtained
by calling the function |
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 |
Return a list with:
ex
: Knots where the
distribution has been estimated
ef
: Discretized values of
the estimated distribution.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | # 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()
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