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

New cylindrical distributions are proposed by combining the sine-skewed von Mises
distribution (circular part) with the Weibull distribution (linear part). This new model, the …

A new hidden Markov model is proposed for the analysis of cylindrical time series, that is,
bivariate time series of intensities and angles. It allows us to segment cylindrical time series …

Motivated by a study from cognitive psychology, we develop a Generalized Linear Model for
circular data within the Bayesian framework, using the von Mises distribution. Although …

We introduce a multivariate hidden Markov model to jointly cluster time‐series observations
with different support, that is, circular and linear. Relying on the general projected normal …

A regression model for correlated circular data is proposed by assuming that samples of
angular measurements are drawn from a multivariate von Mises distribution with mean and …

The modelling of animal movement is an important ecological and environmental issue. It is
well-known that animals change their movement patterns over time, according to observable …

This paper introduces a concomitant-variable hidden semi-Markov model tailored to analyse
marine count data in the Venice lagoon. Our model targets acqua alta events, ie the …

We consider modeling of angular or directional data viewed as a linear variable wrapped
onto a unit circle. In particular, we focus on the spatio-temporal context, motivated by a …

CircSpaceTime is the only R package, currently available, that implements Bayesian models
for spatial and spatio-temporal interpolation of circular data. Such data are often found in …