Results 61 to 70 of about 924,331 (302)
A data driven equivariant approach to constrained Gaussian mixture modeling
, 2016 Maximum likelihood estimation of Gaussian mixture models with different class-specific covariance matrices is known to be problematic. This is due to the unboundedness of the likelihood, together with the presence of spurious maximizers. Existing methods
Di Mari, Roberto +2 more
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Proportionality of Covariance Matrices
The Annals of Statistics, 1987 S\({}_ 0,S_ 1,...,S_ k\) are mutually independent p by p matrices, \(S_ i\) having a Wishart distribution with \(n_ i\) degrees of freedom and expectation \(\Sigma_ i\). The likelihood ratio test of the hypothesis \(\Sigma_ i=\lambda_ i\Sigma_ 0\) for \(i=1,...,k\) is developed.
openaire +2 more sources
bspcov: An R Package for Bayesian sparse covariance matrix estimation
SoftwareXThe bspcov R package provides a Bayesian inference for covariance matrices. The bspcov is developed to aid in research that involves estimating constrained covariance matrices by enabling the use of state-of-the-art Bayesian inference methods.
Kyeongwon Lee +3 more
doaj +1 more source
Penalized maximum likelihood for multivariate Gaussian mixture
, 2001 In this paper, we first consider the parameter estimation of a multivariate random process distribution using multivariate Gaussian mixture law. The labels of the mixture are allowed to have a general probability law which gives the possibility to ...
Mohammad-Djafari, Ali, Snoussi, Hichem
core +3 more sources
Universality of covariance matrices
The Annals of Applied Probability, 2014 In this paper we prove the universality of covariance matrices of the form $H_{N\times N}={X}^{\dagger}X$ where $X$ is an ${M\times N}$ rectangular matrix with independent real valued entries $x_{ij}$ satisfying $\mathbb{E}x_{ij}=0$ and $\mathbb{E}x^2_{ij}={\frac{1}{M}}$, $N$, $M\to \infty$.
Pillai, Natesh S., Yin, Jun
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Spiked sample covariance matrices with possibly multiple bulk components [PDF]
Random Matrices. Theory and Applications, 2017 In this paper, we study the convergent limits and rates of the eigenvalues and eigenvectors for spiked sample covariance matrices whose spectrum can have multiple bulk components.
Xiucai Ding
semanticscholar +1 more source
Genetics and Molecular Biology, 2007 Comparisons of covariance patterns are becoming more common as interest in the evolution of relationships between traits and in the evolutionary phenotypic diversification of clades have grown. We present parallel analyses of covariance matrix similarity
James M. Cheverud, Gabriel Marroig
doaj +1 more source
Monthly Weather Review, 2018 Data assimilation combines forecasts from a numerical model with observations. Most of the current data assimilation algorithms consider the model and observation error terms as additive Gaussian noise, specified by their covariance matricesand ...
P. Tandeo +8 more
semanticscholar +1 more source
Covariance Matrices under Bell-like Detections [PDF]
Open Systems & Information Dynamics, 2013 We derive a simple formula for the transformation of an arbitrary covariance matrix of (n + 2) bosonic modes under general Bell-like detections, where the last two modes are combined in an arbitrary beam splitter (i.e., with arbitrary transmissivity) and then homodyned.
Spedalieri, Gaetana +2 more
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Arthritis Care &Research, Accepted Article.Objective Somatic items used in depression assessments can potentially overlap with symptoms related to physical illness, including systemic sclerosis (SSc). No studies have looked at whether somatic depression items may be influenced by diffuse versus limited SSc disease subtypes, which are associated with varying degrees of symptom presentation.
Sophie Hu +109 more
wiley +1 more source