76
Views
2
CrossRef citations to date
0
Altmetric
Original Articles

Some Bayesian Inferences for Von Mises Distribution

&
Pages 123-137 | Published online: 14 Aug 2013

  • BestD. J. and FisherN. I. (1979). Efficient simulation of the von Mises distribution, Applied Statistics, 28, 152–157.
  • BasuS. and JammalamadakkaS.R. (2000). Unimodality in circular data: A Bayes test, In Advances on Methodoligical and Applied Aspects of Probability and Statistics BalakrishnanN. Ed. 141–153, Taylor & Francis Publishers.
  • CasellaG. and GeorgeE. I. (1992). Explaining the Gibbs sampler, The Journal of American Statistical Association, Vol. 46 (3), 167–174.
  • ChristianC. P. (2001). The Bavesain choice, Springer-Verlag, New York.
  • DamienP. and WalkerS. (1999). A full Bayesian analysis of circular data using the Von Mises distribution. The Canadian J. of Statistics/ la Revue Canadienne de Statistique, 27, 291–298.
  • DevroyeL. (1986). Non-uniform random variate generation., Springer-Verlag.
  • FisherN. I. (1993). Statistical Analysis of Circular data. Cambridge: Cambridge University Press.
  • GemanS. and GemanD. (1984). Stochastic relations, Gibbs distributions, and the Bayesian restoration of images., IEEE transactions on pattern analysis and Machine intelligence, 6, 721–741.
  • GeyerC. J. (1992). Practical Markov Chain Monte Carlo (with discussion). Statistical Science, 7, 473–511.
  • GeyerC. J. (1993). Estimating normalizing constants and reweighting mixtures in Markov Chain Monte Carlo. Technical Report 568, School of Statistics, University of Minnesota.
  • GeyerC. J. and ThompsonE. A. (1992). Constrained Monte Carlo maximum likelihood for dependant data (with discussion), The Journal of Royal Statistical Society, B 54, 657–699.
  • GeyerC. J. and ThompsonE. A. (1995). Annealing Markov Chain Monte Carlo With Applications to pedigree analysis. The Journal of American Statistical Association, 90, 431, 909–920.
  • GilksW. R., RichardsonS. and SpiegelhalterD. J. (1996). Markov Chain Monte Carlo in practice, Chapman & Hall/ CRC, London.
  • HastingsW. K. (1970). Monte Carlo Sampling methods using Markov Chains and their Applications, Biometrika, 57, 97–109.
  • MardiaK. V. (1972). Statistics of Directional Data, Academic Press, New York.
  • MardiaK. V. (1975). Statistics of Directional Data, The Journal of Royal Statistical Society, Series B, 37, 349–393.
  • MardiaK. V. and KentJ. T. (1984). A Goodness of Fit Test for the von Mises-Fisher Distribution, The Journal of Royal Statistical Society, B 46, pp72–78.
  • MetropolisN., RosenbluthA. W., RosenbluthM. N., TellerA. H. and TellerE. (1953). Equations of state calculations by fast computing machines, The Journal of Chemical Physics, 21, 1087–1091.
  • SmithA. F. M. and GelfandA. E. (1992). Bayesian statistics without tears: A sampling-Resampling perspective, The American Statistician, 46, 84–88.
  • SpiegelhalterD. J., BestN. G., GilksW. R. and InskipH. (1995b). Hepatitis B: a case study in MCMC methods. In Markov Chain Monte Carlo in practice (eds. GilksW. R., RichardsonS., and SpiegelhalterD. J.), pp. 21–43. London: Chapman & Hall.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.