scholarly journals Bayesian ranking and selection methods using hierarchical mixture models in microarray studies

Biostatistics ◽  
2009 ◽  
Vol 11 (2) ◽  
pp. 281-289 ◽  
Author(s):  
H. Noma ◽  
S. Matsui ◽  
T. Omori ◽  
T. Sato
Keyword(s):  
Mixture Models ◽  
Ranking And Selection ◽  
Selection Methods ◽  
Hierarchical Mixture Models ◽  
Bayesian Ranking ◽  
Microarray Studies

Nonparametric hierarchical mixture models based on asymmetric Gaussian distribution

2020 ◽  
Vol 106 ◽  
pp. 102829
Author(s):  
Ziyang Song ◽  
Samr Ali ◽  
Nizar Bouguila ◽  
Wentao Fan
Keyword(s):  
Mixture Models ◽  
Gaussian Distribution ◽  
Hierarchical Mixture Models

scholarly journals An overview on selection methods

1982 ◽  
Vol 1 (2) ◽  
pp. 91-96 ◽  
Author(s):  
J. W. H. Swanepoel
Keyword(s):  
Major Part ◽  
Ranking And Selection ◽  
Regression Analyses ◽  
Selection Methods ◽  
Selection Procedures ◽  
Indifference Zone ◽  
Selection Problems ◽  
Fixed Sample ◽  
Sequential Procedures ◽  
Ranking And Selection Procedures

In many studies the experimenter has under consideration several (two or more) alternatives, and is studying them in order to determine which is the best (with regard to certain specified criteria of “goodness”). Such an experimenter does not wish basically to test hypotheses, or construct confidence intervals, or perform regression analyses (though these may be appropriate parts of his analysis); he does wish to select the best of several alternatives, and the major part of his analysis should therefore be directed towards this goal. It is precisely for this problem that ranking and selection procedures were developed. This paper presents an overview of some recent work in this field, with emphasis on aspects important to experimenters confronted with selection problems. Fixed sample size and sequential procedures for both the indifference zone and subset formulations of the selection problem are discussed.

scholarly journals Hierarchical Mixture Models for Expression Profiles

2009 ◽  
pp. 40-52 ◽  
Author(s):  
Michael A. Newton ◽  
Ping Wang ◽  
Christina Kendziorski ◽  
Marina Vannucci
Keyword(s):  
Mixture Models ◽  
Expression Profiles ◽  
Hierarchical Mixture Models

Hierarchical mixture models for biclustering in microarray data

2011 ◽  
Vol 11 (6) ◽  
pp. 489-505 ◽  
Author(s):  
F Martella ◽  
M Alfò ◽  
M Vichi
Keyword(s):  
Mixture Models ◽  
Microarray Data ◽  
Hierarchical Mixture Models
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