Results 201 to 210 of about 3,854 (234)
Some of the next articles are maybe not open access.
Exact fisher information of generalized Dirichlet multinomial distribution for count data modeling
Information Sciences, 2022zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Fatma Najar, Nizar Bouguila
openaire +1 more source
Constructing Multivariate Distributions via the Dirichlet Generator
2020There exist several endeavours proposing a new family of extended distributions using the beta-generating technique. This is a well-known mechanism in developing flexible distributions, by embedding the cumulative distribution function (cdf) of a baseline distribution within the beta distribution that acts as a generator.
Mohammad Arashi +3 more
openaire +1 more source
The principle of interval constraints: A generalization of the symmetric dirichlet distribution
Mathematical Biosciences, 1991A structure for representing problems in decision analysis and in expert systems, which reason under uncertainty, is the influence diagram or causal network. A causal network consists of an underlying joint probability distribution and a directed acyclic graph in which a propositional variable that represents a marginal distribution is stored at each ...
openaire +2 more sources
Value distribution of general Dirichlet series. VII
Lithuanian Mathematical Journal, 2006zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Genys, J. +2 more
openaire +1 more source
2012
In this paper, we introduce a nonparametric Bayesian approach for clustering based on both Dirichlet processes and generalized Dirichlet (GD) distribution. Thanks to the proposed approach, the obstacle of estimating the correct number of clusters is sidestepped by assuming an infinite number of components.
Wentao Fan 0001, Nizar Bouguila
openaire +1 more source
In this paper, we introduce a nonparametric Bayesian approach for clustering based on both Dirichlet processes and generalized Dirichlet (GD) distribution. Thanks to the proposed approach, the obstacle of estimating the correct number of clusters is sidestepped by assuming an infinite number of components.
Wentao Fan 0001, Nizar Bouguila
openaire +1 more source
Regression for compositions based on a generalization of the Dirichlet distribution
Statistical Methods & Applications, 2020zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire +2 more sources
On the value distribution of general Dirichlet series
Annales Polonici MathematiciSummary: We estimate the number of zeros and poles of \(L-\alpha\), where \(L\) is a general Dirichlet series satisfying some conditions and \(\alpha\) is a meromorphic function with \(T(r,\alpha)=o(r)\) as \(r\rightarrow \infty\). In addition, we give a uniqueness theorem in terms of \(a\)-points of Dirichlet series and find Picard exceptional values ...
Lü, Feng, Cao, Zhi, Lü, Weiran
openaire +2 more sources
Laplacian regularized generalized Dirichlet mixture distribution for data clustering
Communications in Statistics - Simulation and Computation, 2018The techniques for data clustering have been frequently applied in machine learning and computer vision, data mining.
Baohua Li, Lixia Hu
openaire +2 more sources
2012
In this paper, we propose a novel Bayesian nonparametric statistical approach of simultaneous clustering and localized feature selection for unsupervised learning. The proposed model is based on a mixture of Dirichlet processes with generalized Dirichlet (GD) distributions, which can also be seen as an infinite GD mixture model.
Wentao Fan 0001, Nizar Bouguila
openaire +2 more sources
In this paper, we propose a novel Bayesian nonparametric statistical approach of simultaneous clustering and localized feature selection for unsupervised learning. The proposed model is based on a mixture of Dirichlet processes with generalized Dirichlet (GD) distributions, which can also be seen as an infinite GD mixture model.
Wentao Fan 0001, Nizar Bouguila
openaire +2 more sources
Processing random processes with generalized Dirichlet distribution
RadioengineeringThe solution of a number of practical problems, such as detection, recognition, etc., involves the use of signal processing procedures invariant with respect to scale parameters. It should be borne in mind that the amplitude of the input signal is either unknown or changes randomly.
V.M. Artyushenko +2 more
openaire +1 more source

