4.8.10.1.7. statsmodels.tsa.varma_process.vargenerate

statsmodels.tsa.varma_process.vargenerate(ar, u, initvalues=None)

generate an VAR process with errors u

similar to gauss uses loop

Parameters:

ar : array (nlags,nvars,nvars)

matrix lagpolynomial

u : array (nobs,nvars)

exogenous variable, error term for VAR

Returns:

sar : array (1+nobs,nvars)

sample of var process, inverse filtered u does not trim initial condition y_0 = 0

Examples

# generate random sample of VAR nobs, nvars = 10, 2 u = numpy.random.randn(nobs,nvars) a21 = np.array([[[ 1. , 0. ],

[ 0. , 1. ]],

[[-0.8, 0. ],

[ 0., -0.6]]])

vargenerate(a21,u)

# Impulse Response to an initial shock to the first variable imp = np.zeros((nobs, nvars)) imp[0,0] = 1 vargenerate(a21,imp)