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statsmodels.sandbox.tsa.fftarma.ArmaFft.generate_sample

ArmaFft.generate_sample(nsample=100, scale=1.0, distrvs=None, axis=0, burnin=0)

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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