generate_sample(nsample=100, scale=1.0, distrvs=None, axis=0, burnin=0)¶
generate ARMA samples
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
rvs : ndarray
random sample(s) of arma process
Should work for n-dimensional with time series along axis, but not tested yet. Processes are sampled independently.