arXiv (Cornell University)
Censored Data Forecasting: Applying Tobit Exponential Smoothing with Time Aggregation
September 2024 • Diego J. Pedregal, Juan R. Trapero
This study introduces a novel approach to forecasting by Tobit Exponential Smoothing with time aggregation constraints. This model, a particular case of the Tobit Innovations State Space system, handles censored observed time series effectively, such as sales data, with known and potentially variable censoring levels over time. The paper provides a comprehensive analysis of the model structure, including its representation in system equations and the optimal recursive estimation of states. It also explores the ben…