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Generalised t-augmented Gaussian mixture modelling using expectation maximisation

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tagmEM

R package for performing generalised t-augmented Gaussian mixture modelling using expectation maximisation

Functions

  • tagm_em - performs univariate t-augmented Gaussian mixture modelling.

Installation

  1. install.packages("devtools")
  2. library(devtools)
  3. install_github("cnfoley/tagmEM", build_opts = c("--no-resave-data", "--no-manual"), build_vignettes = TRUE)
  4. library(tagmEM)
  5. browseVignettes("tagmEM")

Citations

  • Christopher N Foley, Amy M Mason, Paul D W Kirk, Stephen Burgess, MR-Clust: clustering of genetic variants in Mendelian randomization with similar causal estimates, Bioinformatics, 2020;, btaa778, https://doi.org/10.1093/bioinformatics/btaa778
  • A Bayesian Mixture Modelling Approach For Spatial Proteomics Oliver M Crook, Claire M Mulvey, Paul D. W. Kirk, Kathryn S Lilley, Laurent Gatto bioRxiv 282269; doi: https://doi.org/10.1101/282269

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Generalised t-augmented Gaussian mixture modelling using expectation maximisation

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