statsmodels.tsa.arima_process.ArmaProcess.generate_sample
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ArmaProcess.generate_sample(nsample=100, scale=1.0, distrvs=None, axis=0, burnin=0)
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generate ARMA samples
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, then the timeseries is along axis. All other axis have independent arma samples.
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 : ndarray
random sample(s) of arma process
Notes
Should work for n-dimensional with time series along axis, but not tested yet. Processes are sampled independently.
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