Generate synthetic longitudinal correlated data using distributions and correlations from real-world observational data
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Updated
Oct 1, 2024 - R
Generate synthetic longitudinal correlated data using distributions and correlations from real-world observational data
R Package to Perform Clustering of Three-way Count Data Using Mixtures of Matrix Variate Poisson-log Normal Model With Parameter Estimation via MCMC-EM, Variational Gaussian Approximations, or a Hybrid Approach Combining Both.
R Package With Shiny App to Perform and Visualize Clustering of Count Data via Mixtures of Multivariate Poisson-log Normal Model
simstudy: Illuminating research methods through data generation
The data analysis code for the replication study CREP-21-39.
Scripts developed for the Data Visualisation class
A Function for Sequential Clustering of Numerical and Timestamp Data
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