In this example, we demonstrate pyramid’s array differencing, and how it’s used
in conjunction with the
d term to lag a time series.
[-6. -2. 7. 25.] [ 4. 9. 18.] [-8. 5. 32.]
print(__doc__) # Author: Taylor Smith <email@example.com> from pmdarima.utils import array # Build an array and show first order differencing results x = array.c(10, 4, 2, 9, 34) lag_1 = array.diff(x, lag=1, differences=1) # The result will be the same as: x[1:] - x[:-1] print(lag_1) # [-6., -2., 7., 25.] # Note that lag and differences are not the same! If we crank diff up by one, # it performs the same differencing as above TWICE. Lag, therefore, controls # the number of steps backward the ts looks when it differences, and the # `differences` parameter controls how many times to repeat. print(array.diff(x, lag=1, differences=2)) # [4., 9., 18.] # Conversely, when we set lag to 2, the array looks two steps back for its # differencing operation (only one). print(array.diff(x, lag=2, differences=1)) # [-8., 5., 32.] # The lag parameter is controlled by `m`, which is the seasonal periodicity of # a time series. If your series is non-seasonal, lag will typically be 1.
Total running time of the script: ( 0 minutes 0.001 seconds)