We describe and analyse the approach used by Team TinTin (Souhaib Ben Taieb and Rob J Hyndman) in the Load Forecasting track of the Kaggle Global Energy Forecasting Competition 2012. The competition involved a hierarchical load forecasting problem for a US utility with 20 geographical zones. The...

For an additive autoregression model, we study two types of testing problems. First, a parametric specification of a component function is compared against a nonparametric fit. Second, two nonparametric fits of two different time periods are tested for equality. We apply the theory to a...

A multi-input multi-output model is developed by extending the life cycle assessment framework for analysing the relationship between agricultural production and environmental impacts. The inputs include farmland and materials such as fertilisers, pesticides and animals. The outputs are of two...

Motivated by the first-differencing method for linear panel data models, we propose a class of iterative local polynomial estimators for nonparametric dynamic panel data models with or without exogenous regressors. The estimators utilize the additive structure of the first-differenced...

We consider joint rank and variable selection in multivariate regression. Previously proposed joint rank and variable selection approaches assume that different responses are related to the same set of variables, which suggests using a group penalty on the rows of the coefficient matrix....