g_cfar: Generate a CFAR Process

Description Usage Arguments Value References

View source: R/CFAR.r

Description

Generate a convolutional functional autoregressive process.

Usage

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g_cfar(
  tmax = 1001,
  rho = 5,
  phi_list = NULL,
  grid = 1000,
  sigma = 1,
  ini = 100
)

Arguments

tmax

length of time.

rho

parameter for O-U process (noise process).

phi_list

the convolutional function(s). Default is the density function of normal distribution with mean 0 and standard deviation 0.1.

grid

the number of grid points used to construct the functional time series. Default is 1000.

sigma

the standard deviation of O-U process. Default is 1.

ini

the burn-in period.

Value

The function returns a list with components:

cfar

a tmax-by-(grid+1) matrix following a CFAR(p) process.

epsilon

the innovation at time tmax.

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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