The ability to understand and explain the outcomes of data analysis methods, with regard to
aiding decision-making, has become a critical requirement for many applications. For …

Forecasting has always been at the forefront of decision making and planning. The
uncertainty that surrounds the future is both exciting and challenging, with individuals and …

Collections of time series formed via aggregation are prevalent in many fields. These are
commonly referred to as hierarchical time series and may be constructed cross-sectionally …

Determinant attributes play an important role in consumers' purchase decisions. Firms rely
on them to differentiate their products. Determinant attributes are typically identified using …

A series of recent papers introduce the concept of Forecast Reconciliation, a process by
which independently generated forecasts of a collection of linearly related time series are …

Demand forecasts are the basis of most decisions in supply chain management. The
granularity of these decisions lead to different forecast requirements. For example, inventory …

We develop a framework for forecasting multivariate data that follow known linear
constraints. This is particularly common in forecasting where some variables are aggregates …

Intermittent demand forecasting has been widely researched in the context of spare parts
management. However, it is becoming increasingly relevant to many other areas, such as …

In this paper, we build upon a recently proposed forecast combination-based approach to
the reconciliation of a simple hierarchy (Hollyman R., Petropoulos F., Tip** ME …

Do we want coherent hierarchical forecasts, or minimal MAPEs or MAEs? (We won’t get both!)
- ScienceDirect Skip to main contentSkip to article Elsevier logo Journals & Books Search …