statsmodels.tsa.tsatools.lagmat2ds

statsmodels.tsa.tsatools.lagmat2ds(x, maxlag0, maxlagex=None, dropex=0, trim='forward', use_pandas=False)

Generate lagmatrix for 2d array, columns arranged by variables.

Parameters:

• x (array_like) – Data, 2d. Observations in rows and variables in columns.

• maxlag0 (int) – The first variable all lags from zero to maxlag are included.

• maxlagex ({None, int}) – The max lag for all other variables all lags from zero to maxlag are included.

• dropex (int) – Exclude first dropex lags from other variables. For all variables, except the first, lags from dropex to maxlagex are included.

• trim (str) –

  The trimming method to use.

  • ’forward’ : trim invalid observations in front.

  • ’backward’ : trim invalid initial observations.

  • ’both’ : trim invalid observations on both sides.

  • ’none’ : no trimming of observations.

• use_pandas (bool) – If true, returns a DataFrame when the input is a pandas Series or DataFrame. If false, return numpy ndarrays.

Returns:

The array with lagged observations, columns ordered by variable.

Return type:

ndarray

Notes

Inefficient implementation for unequal lags, implemented for convenience.