Applying flat growth

Flat growth is when the trend line is perfectly constant throughout the data. The data's values only differ due to seasonality, holidays, extra regressors, or noise. To see how to model flat growth, let's continue on with our wolf population but this time consider far into the future when the population has fully stabilized.

Let's begin by creating a new dataset, essentially the same as our logistic growth dataset but with a much longer timeframe:

x = pd.to_datetime(pd.date_range('1995-01','2096-02',
                                 freq='M')\
                   .strftime("%Y-%b").tolist())
# create logistic curve
y = [1 / (1 + np.e ** (-.03 * (val...