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Two-way analysis of high-dimensional collinear data
2009
Data mining and knowledge discovery
We present a Bayesian model for two-way ANOVA-type analysis of highdimensional, small sample-size datasets with highly correlated groups of variables. Modern cellular measurement methods are a main application area; typically the task is differential analysis between diseased and healthy samples, complicated by additional covariates requiring a multi-way analysis. The main complication is the combination of high dimensionality and low sample size, which renders classical multivariate techniques
doi:10.1007/s10618-009-0142-5
fatcat:d62mndvfifbfhkjzfhf2zjbjca