opt_bandwidth: Optimal Bandwidth Selection for the Long Run Covariance...

In fChange: Change Point Analysis in Functional Data

Description

This function estimates an optimal window parameter for long run covariance operator estimation in functional time series using the method of Rice G. and Shang H. L. (2017)

Usage

opt_bandwidth(fdobj, kern_type, kern_type_ini, is_change = TRUE, ...)

Arguments

fdobj	Functional data object, class of "fd"
kern_type	Kernel that is used for the long run covariance estimation. The available options are c("BT", "PR", "TH", "QS") where "BT" is Bartlett, "PR" is Parzen, "TH" is Tukey-Hanning, and "QS" is Quadratic Spectral kernel.
kern_type_ini	Initial Kernel function to start the optimal bandwidth search
is_change	If TRUE then the data is centered considering the change in the mean function
...	Further arguments to pass

Value

hat_h_opt	Estimated optimal bandwidth
C_0_est	Estimated Long run covariance kernel using the optimal bandwidth hat_h_opt

References

Rice G. and Shang H. L. (2017), A plug-in bandwidth selection procedure for long run covariance estimation with stationary functional time series, Journal of Time Series Analysis, 38(4), 591-609

See Also

LongRun

Examples

fdata1 = fun_AR(n=100, nbasis=21, order=1, kappa=0.8)
opt_bandwidth(fdata1, "PR", "BT")

fChange documentation built on May 2, 2019, 6:43 a.m.