B_iid_bound: Compute strong white noise confidence bound for...
In wwntests: Hypothesis Tests for Functional Time Series
Description
Usage
Arguments
Value
View source: R/autocorrelation_bound_functions.R
Description
B_iid_bound Computes an approximate asymptotic upper 1-alpha confidence bound for the functional
autocorrelation coefficient at lag h under the assumption that f_data forms a strong white noise
Usage
1
B_iid_bound(f_data, alpha = 0.05)
Arguments
f_data
the functional data matrix with observed functions in the columns
alpha
the significance level to be used in the hypothesis test
Value
Numeric value; the 1-alpha confidence bound for the functional autocorrelation coefficient
at lag h under a strong white noise assumption.
wwntests documentation built on July 2, 2020, 2:57 a.m.
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Description Usage Arguments Value
View source: R/autocorrelation_bound_functions.R
Description
B_iid_bound Computes an approximate asymptotic upper 1-alpha confidence bound for the functional
autocorrelation coefficient at lag h under the assumption that f_data forms a strong white noise
Usage
1 | B_iid_bound(f_data, alpha = 0.05)
|
Arguments
f_data |
the functional data matrix with observed functions in the columns |
alpha |
the significance level to be used in the hypothesis test |
Value
Numeric value; the 1-alpha confidence bound for the functional autocorrelation coefficient at lag h under a strong white noise assumption.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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