long_run_covariance_estimation

Bandwidth estimation in the long-run covariance function for a functional time series, using different types of kernel function

method

Functions for visualizing, modeling, forecasting and hypothesis testing of functional time series.

Han Lin Shang

ftsa

Functional Time Series Analysis

Rob Hyndman

long_run_covariance_estimation function

<dl> <dt>dat</dt>
<dd>A matrix of p by n, where p denotes the number of grid points and n denotes sample size</dd> <dt>C0</dt>
<dd>A tuning parameter used in the adaptive bandwidth selection algorithm of Rice</dd> <dt>H</dt>
<dd>A tuning parameter used in the adaptive bandwidth selection algorithm of Rice</dd></dl>

Arguments

Author

Estimating long-run covariance function for a functional time series — long_run_covariance_estimation

<dl>

 <dt>dat</dt>
<dd>A matrix of p by n, where p denotes the number of grid points and n denotes sample size</dd>

 <dt>C0</dt>
<dd>A tuning parameter used in the adaptive bandwidth selection algorithm of Rice</dd>

 <dt>H</dt>
<dd>A tuning parameter used in the adaptive bandwidth selection algorithm of Rice</dd>

</dl>

long_run_covariance_estimation: Estimating long-run covariance function for a functional time series

Description

Usage

Value

Arguments

Author

References

See Also

Examples