Model fitting and simulation for Gaussian and logistic inner 
    product MultiNeSS models for multiplex networks. The package implements 
    a convex fitting algorithm with fully adaptive parameter tuning, 
    including options for edge cross-validation. For more details see 
    MacDonald et al. (2020).

Functions for the creation/generation and analysis of multilayer social networks <doi:10.18637/jss.v098.i08>.

Analyze multilevel networks as described in Lazega et al (2008)
    <doi:10.1016/j.socnet.2008.02.001> and in Lazega and Snijders 
    (2016, ISBN:978-3-319-24520-1). The package was developed essentially as an 
    extension to 'igraph'.

Network meta-analysis and network meta-regression models for 
    aggregate data, individual patient data, and mixtures of both individual 
    and aggregate data using multilevel network meta-regression as described by
    Phillippo et al. (2020) <doi:10.1111/rssa.12579>. Models are estimated in a
    Bayesian framework using 'Stan'.

Simulating data and fitting multi-species N-mixture models using 'nimble'. Includes features for handling zero-inflation and temporal correlation, Bayesian inference, model diagnostics, parameter estimation, and predictive checks. Designed for ecological studies with zero-altered or time-series data. Mimnagh, N., Parnell, A., Prado, E., & Moral, R. A. (2022) <doi:10.1007/s10651-022-00542-7>. Royle, J. A. (2004) <doi:10.1111/j.0006-341X.2004.00142.x>.

An implementation of a method for building simultaneous confidence intervals for the probabilities of a multinomial distribution given a set of observations, proposed by Sison and Glaz in their paper:
        Sison, C.P and J. Glaz. Simultaneous confidence intervals and sample size determination for multinomial proportions. Journal of the American Statistical Association, 90:366-369 (1995). 
        The method is an R translation of the SAS code implemented by May and Johnson in their paper:
        May, W.L. and W.D. Johnson. Constructing two-sided simultaneous confidence intervals for multinomial proportions for small counts in a large number of cells. Journal of Statistical Software 5(6) (2000). 
        Paper and code available at <DOI:10.18637/jss.v005.i06>.