Renata Rojas

Mathematics

While the global warming clock continues to tick, those responsible for international goals and commitments are racing to reach the deadline set for 2030. Renata Rojas researches statistics and their impact on measuring and forecasting the United Nations Sustainable Development Goals. Graduated in economic sciences from the Federal University of Santa Maria, Renata also completed a master’s degree in production engineering at the Rio Grande do Sul institution. With a PhD in statistics from the Federal University of Pernambuco, the economist has a postdoctoral period at the Federal University of Rio Grande do Norte and another at the Università degli Studi di Pavia, Italy. In 2023, he received the Jan Tinbergen Awards Winners award from the International Statistical Institute (ISI). His research is a reflection of a life oriented towards sustainability. Recently venturing into horticulture, Renata also keeps a compost bin at home and generates her own fertilizer. Passionate about music, statistics reveal that her favourite dimension is the lyrics. Renata enjoys interpreting and researching the lives of various rock and pop lyricists in her free time.

Projects

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