Fits mixed membership models with discrete multivariate data (with
    or without repeated measures) following the general framework of Erosheva et al
    (2004). This package uses a Variational EM approach by approximating the
    posterior distribution of latent memberships and selecting hyperparameters
    through a pseudo-MLE procedure. Currently supported data types are
    Bernoulli, multinomial and rank (Plackett-Luce). The extended GoM model with 
    fixed stayers from Erosheva et al (2007) is now also supported. See Airoldi et al 
    (2014) for other examples of mixed membership models.

The estimation of the parameters in mixed Poisson models.

Tools for the analysis of psychophysical data in R. This package allows to estimate the Point of Subjective Equivalence (PSE) 
    and the Just Noticeable Difference (JND), either from a psychometric function or from a Generalized Linear Mixed Model (GLMM). 
    Additionally, the package allows plotting the fitted models and the response data, simulating psychometric functions of different shapes, and simulating data sets.
    For a description of the use of GLMMs applied to psychophysical data, refer to Moscatelli et al. (2012).

Inference on stochastic differential models Ornstein-Uhlenbeck or
    Cox-Ingersoll-Ross, with one or two random effects in the drift function.

We provide detailed functions for univariate Mixed Tempered Stable distribution.

Functions for creating designs for mixture experiments, making ternary contour plots, and making mixture effect plots.

Evaluation and optimization of the Fisher Information Matrix in NonLinear Mixed Effect Models using Markov Chains Monte Carlo for continuous and discrete data.

Utilizing model-based clustering (unsupervised)
        for functional magnetic resonance imaging (fMRI) data.
        The developed methods (Chen and Maitra (2023) <doi:10.1002/hbm.26425>)
        include 2D and 3D clustering analyses
        (for p-values with voxel locations) and
        segmentation analyses (for p-values alone) for fMRI data where p-values
        indicate significant level of activation responding to stimulate
        of interesting. The analyses are mainly identifying active
        voxel/signal associated with normal brain behaviors.
        Analysis pipelines (R scripts) utilizing this package
        (see examples in 'inst/workflow/') is also implemented with high
        performance techniques.