Results 1 to 10 of about 4,521,299 (288)
Smoothed Dirichlet Distribution
When the cells are ordinal in the multinomial distribution, i.e., when cells have a natural ordering, guaranteeing that the borrowing information among neighboring cells makes sense conceptually.
Lahiru Wickramasinghe +2 more
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A Generalization of the Dirichlet Distribution [PDF]
This paper discusses a generalization of the Dirichlet distribution, the ‘hyperdirichlet’, in which various types of incomplete observations may be incorporated.
Robin K. S. Hankin
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A new statistical method to analyze Morris Water Maze data using Dirichlet distribution [version 2; peer review: 2 approved] [PDF]
The Morris Water Maze (MWM) is a behavioral test widely used in the field of neuroscience to evaluate spatial learning memory of rodents. However, the interpretation of results is often impaired by the common use of statistical tests based on ...
Marianne Maugard +2 more
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A novel diffuse liver nodule detector via integrating semantic edge features and probabilistic uncertainty modeling [PDF]
IntroductionUltrasound image segmentation of diffuse liver fibrosis nodules confronts three critical challenges: boundary ambiguity caused by gradual tissue transitions, texture heterogeneity arising from fibrotic variations, and inadequate uncertainty ...
Lei Tian +4 more
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On Joint Distribution of General Dirichlet Series
In the paper a joint limit theorem in the sense of the weak convergence in the space of meromorphic functions for general Dirichlet series is proved under weaker conditions as in [1].
J. Genys, A. Laurinčikas
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Compositional Data Modeling through Dirichlet Innovations
The Dirichlet distribution is a well-known candidate in modeling compositional data sets. However, in the presence of outliers, the Dirichlet distribution fails to model such data sets, making other model extensions necessary.
Seitebaleng Makgai +2 more
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Assessing Multinomial Distributions with a Bayesian Approach
This paper introduces a unified Bayesian approach for testing various hypotheses related to multinomial distributions. The method calculates the Kullback–Leibler divergence between two specified multinomial distributions, followed by comparing the change
Luai Al-Labadi +3 more
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A Fractional Generalization of the Dirichlet Distribution and Related Distributions [PDF]
This paper is devoted to a fractional generalization of the Dirichlet distribution. The form of the multivariate distribution is derived assuming that the $n$ partitions of the interval $[0,W_n]$ are independent and identically distributed random variables following the generalized Mittag-Leffler distribution. The expected value and variance of the one-
Elvira Di Nardo +2 more
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Parameter Estimation of the Dirichlet Distribution Based on Entropy
The Dirichlet distribution as a multivariate generalization of the beta distribution is especially important for modeling categorical distributions. Hence, its applications vary within a wide range from modeling cell probabilities of contingency tables ...
Büşra Şahin +4 more
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Null Models for Formal Contexts
Null model generation for formal contexts is an important task in the realm of formal concept analysis. These random models are in particular useful for, but not limited to, comparing the performance of algorithms.
Maximilian Felde +2 more
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