g_cfar1 {NTS} | R Documentation |
Generate a CFAR(1) Process
Description
Generate a convolutional functional autoregressive process with order 1.
Usage
g_cfar1(
tmax = 1001,
rho = 5,
phi_func = NULL,
grid = 1000,
sigma = 1,
ini = 100
)
Arguments
tmax |
length of time. |
rho |
parameter for O-U process (noise process). |
phi_func |
convolutional function. Default is 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:
cfar1 |
a tmax-by-(grid+1) matrix following a CFAR(1) 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.
Examples
phi_func= function(x)
{
return(dnorm(x,mean=0,sd=0.1))
}
y=g_cfar1(100,5,phi_func,grid=1000,sigma=1,ini=100)
[Package NTS version 1.1.3 Index]