multgee - GEE Solver for Correlated Nominal or Ordinal Multinomial Responses
GEE solver for correlated nominal or ordinal multinomial responses using a local odds ratios parameterization.
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geemultinomialcpp
6.31 score 9 stars 1 dependents 122 scripts 3.1k downloadsSimCorMultRes - Simulates Correlated Multinomial Responses
Simulates correlated multinomial responses conditional on a marginal model specification.
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binarylongitudinal-studiesmultinomialsimulation
5.62 score 7 stars 2 dependents 389 downloadsShrinkCovMat - Shrinkage Covariance Matrix Estimators
Provides nonparametric Steinian shrinkage estimators of the covariance matrix that are suitable in high dimensional settings, that is when the number of variables is larger than the sample size.
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covariance-matrixshrinkage-estimatorsopenblascppopenmp
4.83 score 8 stars 17 scripts 292 downloadsHDTD - Statistical Inference about the Mean Matrix and the Covariance Matrices in High-Dimensional Transposable Data (HDTD)
Characterization of intra-individual variability using physiologically relevant measurements provides important insights into fundamental biological questions ranging from cell type identity to tumor development. For each individual, the data measurements can be written as a matrix with the different subsamples of the individual recorded in the columns and the different phenotypic units recorded in the rows. Datasets of this type are called high-dimensional transposable data. The HDTD package provides functions for conducting statistical inference for the mean relationship between the row and column variables and for the covariance structure within and between the row and column variables.
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differentialexpressiongeneticsgeneexpressionmicroarraysequencingstatisticalmethodsoftwarebioconductor-packagehigh-dimensionalstatisticsopenblascppopenmp
4.78 score 1 stars 382 downloadsgeer - Bias-Reduced and Penalized Generalized Estimating Equations
Fits marginal regression models for repeated or clustered responses using generalized estimating equations (GEE). Provides ordinary GEE estimators, bias-reduced and bias-corrected GEE estimators, and Jeffreys-type penalized GEE estimators for binary, count and continuous responses. Methods are described in Touloumis (2026a) <doi:10.48550/arXiv.2606.16043> and Touloumis (2026b) <doi:10.48550/arXiv.2606.16058>.
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openblascpp
3.93 score 3 scripts 359 downloads