Results 1 to 10 of about 4,722,571 (139)
A new statistical method to analyze Morris Water Maze data using Dirichlet distribution [version 2; peer review: 2 approved] [PDF]
F1000Research, 2019 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]
Frontiers in Artificial IntelligenceIntroductionUltrasound 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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Compositional Data Modeling through Dirichlet Innovations
Mathematics, 2021 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
Mathematics, 2023 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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Smoothed Dirichlet Distribution
Journal of Statistical Theory and Applications (JSTA), 2023 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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Parameter Estimation of the Dirichlet Distribution Based on Entropy
Axioms, 2023 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
Information, 2020 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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Mathematics, 2022 The high accuracy attainment, using less complex architectures of neural networks, remains one of the most important problems in machine learning. In many studies, increasing the quality of recognition and prediction is obtained by extending neural ...
Ruslan Abdulkadirov +2 more
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Some recent advances in random walks and random environments* [PDF]
ESAIM: Proceedings and Surveys, 2023 Recent contributions to random walks in random environments and related topics are presented. We focus on non parametric estimation for one dimensional random walks in random environment and on the Dirichlet distribution on decomposable graphs.
Devulder Alexis +2 more
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Decay Branch Ratio Sampling Method with Dirichlet Distribution
Energies, 2023 The decay branch ratio is evaluated nuclear data related to the decay heat calculation in reactor safety analysis. Decay branch ratio data are inherently subjected to the “sum-to-one” constraint, making it difficult to generate perturbed samples while ...
Yizhen Wang +5 more
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