Robust inference in time series analysis is concerned with developing statistical methods that remain valid under departures from standard model assumptions, such as the presence of heteroskedasticity ...

This paper investigates new aspects of robust inference for general linear models, calling for a broader array of error measures, beyond the conventional notion of ...

Mixed linear models are used to analyze data in many settings. These models have a multivariate normal formulation in most cases. The maximum likelihood estimator (MLE) or the residual MLE (REML) is ...