B_h_bound: Compute weak white noise confidence bound for autocorrelation...

Description Usage Arguments Value

View source: R/autocorrelation_bound_functions.R

Description

B_h_bound Computes an approximate asymptotic upper 1-alpha confidence bound for the functional autocorrelation coefficient at lag h under a weak white noise assumption.

Usage

1
B_h_bound(f_data, lag, alpha = 0.05, M = NULL, low_disc = FALSE)

Arguments

f_data

the functional data matrix with observed functions in the columns

lag

the lag to use to compute the single lag test statistic

alpha

the significance level to be used in the hypothesis test

M

Number of samples to take when applying a Monte-Carlo approximation

low_disc

Boolean value indicating whether or not to use low-discrepancy sampling in the Monte Carlo method. Note, low-discrepancy sampling will yield deterministic results.

Value

numeric value; the 1-alpha confidence bound for the functional autocorrelation coefficient at lag h under a weak white noise assumption.


wwntests documentation built on July 2, 2020, 2:57 a.m.