est_cfar function

Estimation of a CFAR Process

Estimation of a CFAR process.

est_cfar(f, p = 3, df_b = 10, grid = 1000)

Arguments

• f: the functional time series.
• p: the CFAR order.
• df_b: the degrees of freedom for natural cubic splines. Default is 10.
• grid: the number of gird points used to construct the functional time series and noise process. Default is 1000.

Returns

The function returns a list with components: - phi_coef: the estimated spline coefficients for convolutional function values, a (2*grid+1)-by-p matrix.

• phi_func: the estimated convolutional function(s), a (df_b+1)-by-p matrix.

• rho: estimated rho for O-U process (noise process).

• sigma: estimated sigma for O-U process (noise process).

References

Liu, X., Xiao, H., and Chen, R. (2016) Convolutional autoregressive models for functional time series. Journal of Econometrics, 194, 263-282.