compute_xi_matrix_miaaft: Compute Pairwise Directional Xi-CCF for a Multivariate Matrix
In xiacf: Quantifying Nonlinear Dependence and Lead-Lag Dynamics via Chatterjee's Xi
compute_xi_matrix_miaaft R Documentation
Compute Pairwise Directional Xi-CCF for a Multivariate Matrix
Description
Compute Pairwise Directional Xi-CCF for a Multivariate Matrix
Usage
compute_xi_matrix_miaaft(x, max_lag, n_surr)
Arguments
x
A numeric matrix (rows = time, cols = variables).
max_lag
An integer specifying the maximum positive lag.
n_surr
An integer specifying the number of surrogate datasets.
Value
A list containing flat vectors for lead/lag variable indices, lags,
original Xi values, and a matrix of surrogate Xi values.
xiacf documentation built on April 16, 2026, 5:08 p.m.
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| compute_xi_matrix_miaaft | R Documentation |
Compute Pairwise Directional Xi-CCF for a Multivariate Matrix
Description
Compute Pairwise Directional Xi-CCF for a Multivariate Matrix
Usage
compute_xi_matrix_miaaft(x, max_lag, n_surr)
Arguments
x |
A numeric matrix (rows = time, cols = variables). |
max_lag |
An integer specifying the maximum positive lag. |
n_surr |
An integer specifying the number of surrogate datasets. |
Value
A list containing flat vectors for lead/lag variable indices, lags, original Xi values, and a matrix of surrogate Xi values.
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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