g_cfar | R Documentation |
Generate a convolutional functional autoregressive process.
g_cfar(
tmax = 1001,
rho = 5,
phi_list = NULL,
grid = 1000,
sigma = 1,
ini = 100
)
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. |
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. |
Liu, X., Xiao, H., and Chen, R. (2016) Convolutional autoregressive models for functional time series. Journal of Econometrics, 194, 263-282.
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