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

  • 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.

lagmat – array with lagged observations, columns ordered by variable

Return type:

2d array


Inefficient implementation for unequal lags, implemented for convenience

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© 2006–2008 Scipy Developers
© 2006 Jonathan E. Taylor
Licensed under the 3-clause BSD License.