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» Advances in Mixture Models
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BMCBI
2010
98views more  BMCBI 2010»
15 years 25 days ago
A semi-nonparametric mixture model for selecting functionally consistent proteins
Background: High-throughput technologies have led to a new era of proteomics. Although protein microarray experiments are becoming more common place there are a variety of experim...
Lianbo Yu, R. W. Doerge
94
Voted
GFKL
2007
Springer
148views Data Mining» more  GFKL 2007»
15 years 6 months ago
Mixture Model Based Group Inference in Fused Genotype and Phenotype Data
The analysis of genetic diseases has classically been directed towards establishing direct links between cause, a genetic variation, and effect, the observable deviation of phenot...
Benjamin Georgi, M. Anne Spence, Pamela Flodman, A...
ICPR
2000
IEEE
16 years 1 months ago
Unsupervised Selection and Estimation of Finite Mixture Models
We propose a new method for fitting mixture models that performs component selection and does not require external initialization. The novelty of our approach includes: a minimum ...
Anil K. Jain, Mário A. T. Figueiredo
90
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ICASSP
2009
IEEE
15 years 7 months ago
A complex cross-spectral distribution model using Normal Variance Mean Mixtures
We propose a model for the density of cross-spectral coefficients using Normal Variance Mean Mixtures. We show that this model density generalizes the corresponding marginal dens...
Jason A. Palmer, Scott Makeig, Kenneth Kreutz-Delg...
99
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CSDA
2007
202views more  CSDA 2007»
15 years 20 days ago
Bayesian estimation of the Gaussian mixture GARCH model
In this paper, we perform Bayesian inference and prediction for a GARCH model where the innovations are assumed to follow a mixture of two Gaussian distributions. This GARCH model...
María Concepción Ausín, Pedro...