Some Bayesian Inferences for Von Mises Distribution

SYNOPTIC ABSTRACT

The von Mises distribution (VMS) is considered to be a circular distribution having two parameters and is the natural analogue on the circle of the Normal distribution on the real line. Since the density function involves the modified Bessel function, quite often the sample generation becomes tedious. This limits the applicability of the distribution. In this paper, we have done some Bayesian inferences of the parameters using weighted bootstrap resampling method and a modified version of Gibb's sampling under different prior distributions. A numerical example is also presented.

Keywords and phrases:

• markov chains
• resampling techniques
• prior distribution
• posterior distribution
• weighted bootstrap
• mean direction
• concentration parameter