Don't Throw Out That Winter Coat Yet

Finally, you will forecast the temperature over the next 30 years using an ARMA(1,1) model, including confidence bands around that estimate. Keep in mind that the estimate of the drift will have a much bigger impact on long range forecasts than the ARMA parameters.

Earlier, you determined that the temperature data follows a random walk and you looked at first differencing the data. In this exercise, you will use the ARIMA module on the temperature data (before differencing), which is identical to using the ARMA module on changes in temperature, followed by taking cumulative sums of these changes to get the temperature forecast.

The data is preloaded in a DataFrame called temp_NY.

Create an instance of the ARIMA class called mod for an integrated ARMA(1,1) model
- The d in order(p,d,q) is one, since we first differenced once
- Fit mod using the .fit() method and call the results res
Forecast the series using the plot_predict() method on res
- Choose the start date as 1872-01-01 and the end date as 2046-01-01

Exercise

Don't Throw Out That Winter Coat Yet

Instructions