JOURNAL ARTICLE

Parameter estimation for the bivariate wrapped normal distribution

Abstract

Correlated uncertain angular quantities can be modeled using the bivariate wrapped normal distribution. In this paper, we focus on the problem of estimating the distribution's parameters from a given set of samples. For this purpose, we propose several new parameter estimation methods and compare them to estimation techniques found in literature. All methods are thoroughly evaluated in simulations. One of the novel methods is shown to combine the advantages of maximum likelihood estimation and moment-based methods, thus outperforming current state-of-the-art techniques.

Keywords:
Bivariate analysis Maximum likelihood Moment (physics) Focus (optics) Estimation theory Method of moments (probability theory) Distribution (mathematics) Computer science Estimation Mathematics Set (abstract data type) Algorithm Mathematical optimization Applied mathematics Statistics Mathematical analysis Engineering Physics

Metrics

8
Cited By
1.26
FWCI (Field Weighted Citation Impact)
28
Refs
0.91
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Target Tracking and Data Fusion in Sensor Networks
Physical Sciences →  Computer Science →  Artificial Intelligence
Control Systems and Identification
Physical Sciences →  Engineering →  Control and Systems Engineering
Bayesian Methods and Mixture Models
Physical Sciences →  Computer Science →  Artificial Intelligence

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