# nonlinear_process¶

hyppo.tools.nonlinear_process(n, lag=1, phi=1, sigma=1)

2 nonlinearly dependent time series simulation.

$$X_t$$ and $$Y_t$$ are together a bivariate nonlinear process. Noise follows $$\mathcal{N}(0, \sigma)$$. With lag (1), this is

$\begin{split}\begin{bmatrix} X_t \\ Y_t \end{bmatrix} = \begin{bmatrix} \phi \epsilon_t Y_{t - 1} \\ \eta_t \end{bmatrix}\end{split}$
Parameters
Returns

x,y (ndarray) -- Simulated data matrices. x and y have shape (n,) where n is the number of samples.