statsmodels.tsa.tsatools.lagmat2ds

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

Generate lagmatrix for 2d array, columns arranged by variables

Parameters:	x (array_like, 2d) – 2d data, observation in rows and variables in columns maxlag0 (int) – for first variable all lags from zero to maxlag are included maxlagex (None or int) – max lag for all other variables all lags from zero to maxlag are included dropex (int (default is 0)) – exclude first dropex lags from other variables for all variables, except the first, lags from dropex to maxlagex are included trim (string) – ‘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, optional) – If true, returns a DataFrame when the input is a pandas Series or DataFrame. If false, return numpy ndarrays.
Returns:	lagmat – array with lagged observations, columns ordered by variable
Return type:	2d array

Notes

Inefficient implementation for unequal lags, implemented for convenience