Description Usage Arguments Value Examples
Simulate n
observarions multivariate autoregressive time series, i.e.
X_t = ∑_{k=0}^p A_k X_{t-k} + \varepsilon_t,
where \varepsilon_t is a d
-dimensional white noise and A_k are d \times d matrices
and X_t = 0 for t ≤q 0.
1 |
n |
number of observations to generate |
d |
dimension of the process |
Psi |
serie of regression operators (if one matrix is given it is treated as regressor with lag 1) |
first |
the first element of a series |
noise |
the noise we want to add |
sd |
standard deviation of the gaussian noise if the noise wasn't provided |
an AR series of vectors
1 2 3 4 5 6 7 |
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