statsmodels.tsa.arima_process.ArmaProcess.generate_sample

ArmaProcess.generate_sample(nsample=100, scale=1.0, distrvs=None, axis=0, burnin=0) [source]

Simulate an ARMA

Parameters:	nsample (int or tuple of ints) – If nsample is an integer, then this creates a 1d timeseries of length size. If nsample is a tuple, creates a len(nsample) dimensional time series where time is indexed along the input variable axis. All series are unless distrvs generates dependent data. scale (float) – standard deviation of noise distrvs (function, random number generator) – function that generates the random numbers, and takes sample size as argument default: np.random.randn TODO: change to size argument burnin (integer (default: 0)) – to reduce the effect of initial conditions, burnin observations at the beginning of the sample are dropped axis (int) – See nsample.
Returns:	rvs – random sample(s) of arma process
Return type:	ndarray

Notes

Should work for n-dimensional with time series along axis, but not tested yet. Processes are sampled independently.