On initial direction, orientation and discreteness in the analysis of circular variables
@article{Mastrantonio2015OnID, title={On initial direction, orientation and discreteness in the analysis of circular variables}, author={Gianluca Mastrantonio and Giovanna Jona Lasinio and Antonello Maruotti and Gianfranco Calise}, journal={arXiv: Methodology}, year={2015} }
In this paper, we propose a discrete circular distribution obtained by extending the wrapped Poisson distribution. This new distribution, the Invariant Wrapped Poisson (IWP), enjoys numerous advantages: simple tractable density, parameter-parsimony and interpretability, good circular dependence structure and easy random number generation thanks to known marginal/conditional distributions. Existing discrete circular distributions strongly depend on the initial direction and orientation, i.e. a…
3 Citations
Discrete Circular Distributions with Applications to Shared Orthologs of Paired Circular Genomes
- Biology
- 2020
The result that different DCDs fit the shared orthologs is consistent with the fact they belong to two kingdoms, and this finding is important for building synthetic prokaryotic genomes in synthetic biology.
Hidden Markov model for discrete circular–linear wind data time series
- Computer Science, Mathematics
- 2016
This work deals with a bivariate time series of wind speed and direction with a non-parametric Bayesian hidden Markov model, introducing a new emission distribution suitable to model the data, based on the invariant wrapped Poisson, the Poisson and the hurdle density.
On the Analysis of PM/FM Noise Radar Waveforms Considering Modulating Signals with Varied Stochastic Properties
- Computer ScienceSensors
- 2021
This paper investigates the performance of several random phase and frequency modulated waveforms, varying the stochastic properties of their modulating signals.
References
SHOWING 1-10 OF 30 REFERENCES
Spatio-temporal circular models with non-separable covariance structure
- Computer Science
- 2016
This work accommodates covariates, implements full kriging and forecasting, and also allows for a nugget which can be time dependent, within a Bayesian framework, to facilitate Markov chain Monte Carlo model fitting.
A hidden Markov approach to the analysis of space–time environmental data with linear and circular components
- MathematicsStochastic Environmental Research and Risk Assessment
- 2014
A multivariate hidden Markov model that includes features of the data within a single framework, associated with easily interpretable components of large-scale and small-scale spatial variation, and provides a parsimonious representation of the sea surface in terms of alternating environmental states.
Bayesian hidden Markov modelling using circular‐linear general projected normal distribution
- Mathematics
- 2014
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 distribution,…
Directional Statistics, I
- Mathematics
- 2011
In many natural and physical sciences the measurements are directions—either in two- or three-dimensions. This chapter briefly introduces this novel area of statistics, and provides a good starting…
Inference for circular distributions and processes
- Computer Science, MathematicsStat. Comput.
- 1998
The power and flexibility of Markov chain Monte Carlo methods to fit such classes of models to circular data and applications are given to multivariate and time series data of wind directions.
Wrapped Skew Laplace Distribution on Integers:A New Probability Model for Circular Data
- Mathematics
- 2012
In this paper we propose a new family of circular distributions, obtained by wrapping discrete skew Laplace distribution on Z = 0, ±1, ±2, around a unit circle. In contrast with many wrapped…
New Families of Wrapped Distributions for Modeling Skew Circular Data
- Mathematics
- 2004
Abstract We discuss circular distributions obtained by wrapping the classical exponential and Laplace distributions on the real line around the circle. We present explicit forms for their densities…
Spatial analysis of wave direction data using wrapped Gaussian processes
- Environmental Science, Computer Science
- 2012
A model-based approach to handle periodic data in the case of measurements taken at spatial locations, anticipating structured dependence between these measurements, and formulates a wrapped Gaussian spatial process model for this setting.
A hidden Markov model for the analysis of cylindrical time series
- Mathematics
- 2015
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 according…
Modeling Space and Space-Time Directional Data Using Projected Gaussian Processes
- Computer Science
- 2014
The contribution is to develop a fully model-based approach to capture structured spatial dependence for modeling directional data at different spatial locations, and builds a projected Gaussian spatial process, induced from an inline bivariate Gaussia spatial process.