Dynamic models for doubly limited random variables: how to predict sustainable development indicators measured in rates and proportions?

Science / Mathematics

Doubly limited data are those that have a minimum value and a maximum value, and the most common examples are rates and proportions. When studying the Sustainable Development Goals (SDGs) and the United Nations 2030 Agenda, the indicators used are almost mainly composed of proportions of the population of interest. Furthermore, as these are objectives to be achieved by 2030, there is a need to monitor these indicators over time. Thus, this project combines doubly limited probability distributions with time series models for monitoring the SDGs. Another commitment is the sharing of computational codes. With this, the new models can overcome the barriers of mathematics and be applied by data scientists outside the academic environment.

Open Calls

Chamada 6