# Efficient Evaluation of the Probability Density Function of a Wrapped Normal Distribution

arXiv: https://arxiv.org/abs/1405.6397 · HTML: https://mlsanity.com/paper/1405.6397/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 May 2014.

## Built on by (most cited first, 4 of 4)

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- [Motron: Multimodal Probabilistic Human Motion Forecasting](https://mlsanity.com/paper/2203.04132/) (2022)
- [A Periodic Bayesian Flow for Material Generation](https://mlsanity.com/paper/2502.02016/) (2025)
- [Adaptive and Robust Watermark for Generative Tabular Data](https://mlsanity.com/paper/2409.14700/) (2024)

## Abstract (arXiv)

The wrapped normal distribution arises when a the density of a one-dimensional normal distribution is wrapped around the circle infinitely many times. At first look, evaluation of its probability density function appears tedious as an infinite series is involved. In this paper, we investigate the evaluation of two truncated series representations. As one representation performs well for small uncertainties whereas the other performs well for large uncertainties, we show that in all cases a small number of summands is sufficient to achieve high accuracy.
