Fit a time series model for the data set. Use the model to predict for next 12 time periods. Also for each model compute RMSE (root mean squared error). You need to split the data in to training set (90%) and test set (10%).

Data description: Average temperature (in F) of Tennessee from Jan-1895 to Mar-2019 (Monthly data).

File Name: Climate.txt

Source:https://www.ncdc.noaa.gov/cag/statewide/time-series/40/tavg/all/3/1895-2019?base_prd=true&firstbaseyear=1930&lastbaseyear=2000

Variables: Date: Time associated with the sample

Values: Average Temperature

Anomaly: Departure from a reference value or long-termaverage.

You need to fit a time series model using the variable Values. You can remove the other two variables from the data.