In this paper, we derive elementary M- and optimally robust asymptotic linear (AL)-estimates for the parameters of an Ornstein–Uhlenbeck process. Simulation and estimation of the process are already well-studied, see Iacus (Simulation and inference for stochastic differential equations....

Typical heart rate variability (HRV) times series are cluttered with outliers generated by measurement errors, artifacts and ectopic beats. Robust estimation is an important tool in HRV analysis, since it allows clinicians to detect arrhythmia and other anomalous patterns by reducing the impact...

Insee's quarterly survey of investment in industry is a prime source of information concerning short-term evolutions in productive investment, making it possible to estimate these evolutions at an early stage and with considerable precision. However, the annual nature of the questions posed...

In recent years, a number of authors have considered extensions of classical unit root tests to cases where the process is driven by infinite variance innovations, as well as considering their asymptotic properties. Unfortunately, these extensions are typically inefficient as they do not exploit...

We discuss the asymptotic linearization of multivariate M-estimators, when the limit distribution is stable. We consider two different types of kernels: VC and bracketing. When applied to the case of normal limits, our work improves the known results to obtain the limit distribution of...