est_cfar: Estimation of a CFAR Process

Description Usage Arguments Value References

View source: R/CFAR.r

Description

Estimation of a CFAR process.

Usage

1
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.

Value

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.


NTS documentation built on Aug. 6, 2020, 5:08 p.m.

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