long_run_covariance {fChange} | R Documentation |
Estimate Long-run Covariance Kernel
Description
Estimate the long-run covariance kernel for functional data. That is, solve
C_{\epsilon}(t,t') = \sum_{l=-\inf}^{\inf} \text{Cov}(\epsilon_0(t),
\epsilon_l(t'))
with sequence (\epsilon_i : i \in \mathbb{Z})
defined as the centered
data (can center based on changes if given).
Usage
long_run_covariance(
X,
h = 2 * ncol(X)^(1/5),
K = bartlett_kernel,
changes = NULL
)
Arguments
X |
A dfts object or data which can be automatically converted to that
format. See |
h |
The window parameter parameter for the estimation of the long run
covariance kernel. The default value is |
K |
Function indicating the kernel to use if |
changes |
Vector of numeric change point locations. Can be NULL. |
Value
Symmetric data.frame of numerics with dim of ncol(data) x ncol(data).
Examples
result <- long_run_covariance(electricity, 2)