Background: Recently several statistical methods have been proposed to identify genes with differential expression between two conditions. However, very few studies consider the p...
—This paper studies the problem of outlier detection on uncertain data. We start with a comprehensive model considering both uncertain objects and their instances. An uncertain o...
Principal component analysis (PCA) is a classical data analysis technique that finds linear transformations of data that retain the maximal amount of variance. We study a case whe...
In the statistical approach for self-organizing maps (SOMs), learning is regarded as an estimation algorithm for a Gaussian mixture model with a Gaussian smoothing prior on the ce...
Estimating an overall density function from repeated observations on each of a sample of independent subjects or experimental units is of interest. An example is provided by biodem...