Results 21 to 30 of about 121,868 (329)
On Johnson’s “Sufficientness” Postulates for Feature-Sampling Models
Mathematics, 2021 In the 1920s, the English philosopher W.E. Johnson introduced a characterization of the symmetric Dirichlet prior distribution in terms of its predictive distribution. This is typically referred to as Johnson’s “sufficientness” postulate, and it has been
Federico Camerlenghi, Stefano Favaro
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Efficient Feature Mapping in Classifying Proportional Data
IEEE Access, 2021 In image classification, traditional kernels or feature mapping functions of Support Vector Machine(SVM) use discriminative features without considering the true nature of the data.
Md. Hafizur Rahman, Nizar Bouguila
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Sensors, 2018 Today IoT integrate thousands of inter networks and sensing devices e.g., vehicular networks, which are considered to be challenging due to its high speed and network dynamics.
Muhammad Sohail, Liangmin Wang
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Modeling the Dirichlet distribution using multiplicative functions
Nonlinear Analysis, 2020 For q,m,n,d ∈ N and some multiplicative function f > 0, we denote by T3(n) the sum of f(d) over the ordered triples (q,m,d) with qmd = n. We prove that Cesaro mean of distribution functions defined by means of T3 uniformly converges to the one-parameter ...
Gintautas Bareikis, Algirdas Mačiulis
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The two-parameter Poisson--Dirichlet point process [PDF]
, 2009 The two-parameter Poisson--Dirichlet distribution is a probability distribution on the totality of positive decreasing sequences with sum 1 and hence considered to govern masses of a random discrete distribution.
Handa, Kenji
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A characterization of Dirichlet distributions
Journal of Multivariate Analysis, 1988 \textit{J. N. Darroch} and \textit{D. Ratcliff} [J. Am. Stat. Assoc. 66, 641- 643 (1971; Zbl 0228.62009)] have given a characterization of the Dirichlet distributions based on the properties of independence of various functions of the random variables \((X_ 1,X_ 2,...,X_ k)\) having a joint continuous distribution over the k-dimensional simplex: \(0 ...
Rao, B.V, Sinha, Bikas K
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New statistical inference for the Weibull distribution [PDF]
Tutorials in Quantitative Methods for Psychology, 2015 Weibull distribution has become a popular tool for modeling life data and improving growth in the field of reliability. The successful application of Weibull distribution to real data depends on the statistical power of hypotheses tests to a large extent.
Zhao, X. +4 more
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Understanding Hierarchical Processes
Entropy, 2022 Hierarchical stochastic processes, such as the hierarchical Dirichlet process, hold an important position as a modelling tool in statistical machine learning, and are even used in deep neural networks.
Wray Buntine
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The supervised hierarchical Dirichlet process [PDF]
, 2014 We propose the supervised hierarchical Dirichlet process (sHDP), a nonparametric generative model for the joint distribution of a group of observations and a response variable directly associated with that whole group.
Dai, Andrew M., Storkey, Amos J.
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Properties of Noncentral Dirichlet Distributions
Computers & Mathematics with Applications, 2006 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Sánchez, L.E., Nagar, D.K., Gupta, A.K.
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