Results 21 to 30 of about 4,521,299 (288)
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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On Pearson–Kotz Dirichlet distributions
Journal of Multivariate Analysis, 2011 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
N. Balakrishnan 0002, Enkelejd Hashorva
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Properties of Noncentral Dirichlet Distributions
Computers & Mathematics with Applications, 2006 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
L. E. Sánchez +2 more
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Lattice permutations and Poisson-Dirichlet distribution of cycle lengths [PDF]
, 2012 We study random spatial permutations on ℤ3 where each jump x↦π(x) is penalized by a factor e−T∥x−π(x)∥2 . The system is known to exhibit a phase transition for low enough T where macroscopic cycles appear.
Daniel Ueltschi +6 more
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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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Countable representation for infinite-dimensional diffusions derived from the two parameter Poisson Dirichlet process [PDF]
, 2009 This paper provides a countable representation for a class of infinite-dimensional diffusions which extends the infinitely-many-neutral-alleles model and is related to the two-parameter Poisson-Dirichlet process. By means of Gibbs sampling procedures, we
Ruggiero, Matteo +3 more
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A truncated bivariate inverted Dirichlet distribution
Statistica, 2013 A truncated version of the bivariate inverted dirichlet distribution is introduced. Unlike the inverted dirichlet distribution, this possesses finite moments of all orders and could therefore be a better model for certain practical situations.
Saralees Nadarajah
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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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Sampling from Dirichlet process mixture models with unknown concentration parameter: mixing issues in large data implementations [PDF]
, 2014 We consider the question of Markov chain Monte Carlo sampling from a general stick-breaking Dirichlet process mixture model, with concentration parameter (Formula presented.).
Silvia Liverani +5 more
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Generalised Dirichlet-Type Distributions [PDF]
The Egyptian Statistical Journal, 1985 Series of independent life tests based on exponential model are considered. The distribution of a linear combination of spacings (LCOS) as well as the distribution of the sum of LCOS are used to develop new distributions which are generalised Dirichlet ...
G.S. Lingappaiah
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