Modeling Information Content Via Dirichlet-Multinomial Regression Analysis
Sign Up to like & getrecommendations! Published in 2017 at "Multivariate Behavioral Research"
DOI: 10.1080/00273171.2017.1279957
Abstract: ABSTRACT Shannon entropy is being increasingly used in biomedical research as an index of complexity and information content in sequences of symbols, e.g. languages, amino acid sequences, DNA methylation patterns and animal vocalizations. Yet, distributional… read more here.
Keywords: information; entropy; multinomial regression; information content ... See more keywords
Batch effects correction for microbiome data with Dirichletâmultinomial regression
Sign Up to like & getrecommendations! Published in 2019 at "Bioinformatics"
DOI: 10.1093/bioinformatics/bty729
Abstract: Motivation: Metagenomic sequencing techniques enable quantitative analyses of the microbiome. However, combining the microbial data from these experiments is challenging due to the variations between experiments. The existing methods for correcting batch effects do not… read more here.
Keywords: bdmma; multinomial regression; microbiome data; batch ... See more keywords
Sparse Count Data Clustering Using an Exponential Approximation to Generalized Dirichlet Multinomial Distributions
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Neural Networks and Learning Systems"
DOI: 10.1109/tnnls.2020.3027539
Abstract: Clustering frequency vectors is a challenging task on large data sets considering its high dimensionality and sparsity nature. Generalized Dirichlet multinomial (GDM) distribution is a competitive generative model for count data in terms of accuracy,… read more here.
Keywords: generalized dirichlet; count; exponential family; dirichlet multinomial ... See more keywords