View source: R/data_simulations.R
far_1_S | R Documentation |
'far_1_S' Simulates an FAR(1,S)-fGARCH(1,1) process with N independent observations, each observed discretely at J points on the interval [0,1].
far_1_S(N, J, S, type = "IID", burn_in = 50)
N |
the number of fGARCH(1,1) curves to sample. |
J |
the number of points at which each curve is sampled (the resolution of the data). |
S |
the autoregressive operator of the model, between 0 and 1, indicating the level of conditional heteroscedasticity. |
type |
the assumed model of the error term. The default argument is 'IID', under which the errors are assumed to be independent and identically distributed. The alternative argument is 'fGARCH', which will assume that the errors follow an fGARCH(1,1) process. |
burn_in |
the number of initial samples to burn (discard). |
A J x N matrix containing FAR(1,S) functional data in the columns.
f <- far_1_S(100, 50, 0.75)
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