Building a Life Expectancy Trends ARIMA Model in Python

Studying life expectancy is crucial for understanding demographic trends, public health planning, and policy development. I developed an ARIMA model used for forecasting life expectancy trends based on calendar-year and birth-cohort data. It covers the data preprocessing steps, model fitting and parameter selection process, as well as the forecasting and evaluation results. You may download my models and data files from my GitHub following the link below. The Python code is uploaded into https://github.com/AIMLModeling/LifeExpectation