Mainstream statistical methodology is generally applicable to data observed in Euclidean
space. There are, however, numerous contexts of considerable scientific interest in which …

Circular data can be found across many areas of science, for instance meteorology (eg,
wind directions), ecology (eg, animal movement directions), or medicine (eg, seasonality in …

Time series on the unit n-sphere arise in directional statistics, compositional data analysis,
and many scientific fields. There are few models for such data, and the ones that exist suffer …

The need for regression models to predict circular values arises in many scientific fields. In
this work we explore a family of expressive and interpretable distributions over circle-valued …

The elaborate description of passenger travel profiles is of significant importance in urban
planning, socioeconomic structural design, and individual travel preference analysis …

Climbing plants rely on suitable support to provide the light conditions they require in the
canopy. Negative phototropism is a directional search behavior proposed to detect a support …

Accurate wind pattern modelling is crucial for various applications, including renewable
energy, agriculture, and climate adaptation. In this paper, we introduce the wrapped …

Pesticides play an important role in modern-day agriculture by protecting produce from pests
and diseases. Nonetheless, exposure to these biological agents poses a significant public …

Directional or periodic measurements play a vital role in many scientific fields. Developing
ways to analyze directional data while accounting for their specific characteristics is an …

Spatial direction vector data can be represented cylindrically by linear magnitudes and
circular angles. We analyze such data by using a hierarchical Markov random field model …