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Estimator for Number of Sources using Minimum Description Length Criterion for Blind Sparse Source Mixtures
Minimum Description Length Criterion Blind Sparse Source Mixtures
2015/9/29
In this paper I present a Minimum Description Length Estimator for number of sources in an anechoic mixture of sparse signals.The criterion is roughly equal to the sum of negative normalized maximum l...
Higher Criticism for Detecting Sparse Heterogeneous Mixtures
Multiple Comparsions Combining Many p-values
2015/8/21
Higher Criticism, or second-level significance testing, is a multiple comparisons concept
mentioned in passing by Tukey (1976). It concerns a situation where there are many independent tests of...
Clustering with mixtures of log-concave distributions
EM algorithm Log-concave distribution Clustering Normal copula
2015/8/20
The EM algorithm is a popular tool for clustering observations via a parametric mixture model. Two disadvantages of this
approach are that its success depends on the appropriateness of the assumed pa...
Fitting directed acyclic graphs with latent nodes as finite mixtures models, with application to education transmission
Extendedlatentclassmodels mixturemodels structuralequations causal inference
2012/11/22
This paper describes an efficient EM algorithm for maximum likelihood estimation of a system of nonlinear structural equations corresponding to a directed acyclic graph model that can contain an arbit...
The disentangling number for phylogenetic mixtures
disentangling number phylogenetic mixtures Combinatorics
2011/9/8
Abstract: We provide a logarithmic upper bound for the disentangling number on unordered lists of leaf labeled trees. This results is useful for analyzing phylogenetic mixture models. The proof depend...
A generalized Isserlis theorem for location mixtures of Gaussian random vectors
Isserlis theorem normal-variance mixture generalized hyperbolic distribution
2011/9/2
Abstract: In a recent paper, Michalowicz et al. provide an extension of Isserlis theorem to the case of a Bernoulli location mixture of a Gaussian vector. We extend here this result to the case of any...
Decision Based Uncertainty Propagation Using Adaptive Gaussian Mixtures
Adaptive Gaussian Sum Decision Making Uncertainty Propagation Expected Loss
2011/9/29
Abstract: Given a decision process based on the approximate probability density function returned by a data assimilation algorithm, an interaction level between the decision making level and the data ...
Primal-dual splitting algorithm for solving inclusions with mixtures of composite, Lipschitzian, and parallel-sum monotone operators
maximal monotone operator monotone inclusion nonsmooth convex optimization parallel sum set-valued duality splitting algorithm
2011/8/22
Abstract: We propose a primal-dual splitting algorithm for solving monotone inclusions involving a mixture of sums, linear compositions, and parallel sums of set-valued and Lipschitzian operators. An ...
Well posedness of an isothermal diffusive model for binary mixtures of incompressible fluids
Diffuse interface model Cahn-Hilliard-Navier-Stokes equations
2011/1/20
e consider a model describing the behavior of a mixture of two incompressible fluids with the same density in isothermal conditions. The model consists of three balance equations: continuity equation,...
We present a mixture Poisson model for claims counts in which the number of components in the mixture are estimated by reversible jump MCMC methods.
Applied statistics in designing special organic mixtures
mean standard deviation correlation variation
2009/1/7
Samples of toilet soaps were produced by saponi¯cation of
di®erent mixture of palm oil (PO) and palm kernel oil (PKO). The pro-
duced soaps were analyzed for their total free matter (TFM), ...