Results 301 to 310 of about 123,391 (326)

The Poisson-Dirichlet distribution

1992
Abstract The parameters α j may take any strictly positive values, and the character of the distribution changes markedly as these vary. If α j = 1 for all j we have the uniform distribution on Δ n If the α j = are large, (9.3) concentrates probability well away from the boundaries of Δ n, corresponding to distributions p which are ...
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On the distribution of points in a poisson dirichlet process

Journal of Applied Probability, 1988
A probability density function important in the Poisson Dirichlet process of population genetics is studied. An accurate computational algorithm is given for this density and for the marginal distributions of the points in the Poisson Dirichlet process. The distribution of the maximal point of the process is tabulated.
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Interpreting Belief Functions as Dirichlet Distributions

2007
Traditional Dempster Shafer belief theory does not provide a simple method for judging the effect of statistical and probabilistic data on belief functions and vice versa. This puts belief theory in isolation from probability theory and hinders fertile cross-disciplinary developments, both from a theoretic and an application point of view.
Audun Jøsang, Zied Elouedi
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The Poisson–Dirichlet Distribution

2010
The focus of this chapter is the Poisson–Dirichlet distribution, the central topic of this book. We introduce this distribution and discuss various models that give rise to it. Following Kingman (J. Roy. Statist. Soc. B 37:1–22, 1975), the distribution is constructed through the gamma process. An alternative construction in (R. Arratia, A.D.
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Integrating patent analysis into technology roadmapping: A latent dirichlet allocation based technology assessment and roadmapping in the field of Blockchain

Technological Forecasting and Social Change, 2021
Tugrul U Daim, Yunqiu Zhang
exaly  

Estimating Normal Means with a Dirichlet Process Prior

Journal of the American Statistical Association, 1994
Michael Escobar
exaly  

Variational Bayesian Learning for Dirichlet Process Mixture of Inverted Dirichlet Distributions in Non-Gaussian Image Feature Modeling

IEEE Transactions on Neural Networks and Learning Systems, 2019
Zhanyu Ma, Yuping Lai, W Bastiaan Kleijn   +2 more
exaly  

Dirichlet Distribution

2008
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Sampling the Dirichlet Mixture Model with Slices

Communications in Statistics Part B: Simulation and Computation, 2007
Stephen G Walker
exaly  

Dirichlet and Related Distributions

2011
Kai Wang Ng, Guo‐Liang Tian, Man‐Lai Tang   +2 more
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