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  • Search: subject:"MCMC computation"
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Year of publication
Subject
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MCMC computation 3 Clustering 2 Microarray analysis 2 Mixture distributions 2 Multiple hypothesis testing 2 Non-central t-distribution 2 Microarray data analysis 1 Multidimensional scaling 1 Neural network 1 Spatial Bayesian methods 1
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Online availability
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Free 2 Undetermined 1
Type of publication
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Book / Working Paper 2 Article 1
Language
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English 2 Undetermined 1
Author
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Marín, J.M. 1 Marín, Juan Miguel 1 Marín, Miguel J. 1 Nieto, Carmen 1 Rodríguez-Bernal, M. Teresa 1 Rodríguez-Bernal, M.T. 1
Institution
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Departamento de Estadistica, Universidad Carlos III de Madrid 2
Published in...
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Statistics and Econometrics Working Papers 2 Computational Statistics & Data Analysis 1
Source
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RePEc 3
Showing 1 - 3 of 3
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Multiple hypothesis testing and clustering with mixtures of non-central t-distributions applied in microarray data analysis
Marín, Miguel J.; Rodríguez-Bernal, M. Teresa - Departamento de Estadistica, Universidad Carlos III de … - 2010
Multiple testing analysis, based on clustering methodologies, is usually applied in Microarray Data Analysis for comparisons between pair of groups. In this paper, we generalize this methodology to deal with multiple comparisons among more than two groups obtained from microarray expressions of...
Persistent link: https://www.econbiz.de/10008692050
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Bayesian non-linear matching of pairwise microarray gene expressions
Marín, Juan Miguel; Nieto, Carmen - Departamento de Estadistica, Universidad Carlos III de … - 2008
In this paper, we present a Bayesian non-linear model to analyze matching pairs of microarray expression data. This model generalizes, in terms of neural networks, standard linear matching models. As a practical application, we analyze data of patients with Acute Lymphoblastic Leukemia and we...
Persistent link: https://www.econbiz.de/10008480484
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Multiple hypothesis testing and clustering with mixtures of non-central t-distributions applied in microarray data analysis
Marín, J.M.; Rodríguez-Bernal, M.T. - In: Computational Statistics & Data Analysis 56 (2012) 6, pp. 1898-1907
Multiple testing analysis and clustering methodologies are usually applied in microarray data analysis. A combination of both methods to deal with multiple comparisons among groups obtained from microarray expressions of genes is proposed. Assuming normal data, a statistic which depends on...
Persistent link: https://www.econbiz.de/10011056509
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