Interchangeable Gaussian Process Models (IGP)
Creates a Gaussian process model using the specified package. Makes it easy to try different packages in same code, only the package argument needs to be changed. It is essentially a wrapper for the other Gaussian process software packages.

Signal Extraction Approach for Sparse Multivariate Response Regression (SiER)
Methods for regression with high-dimensional predictors and univariate or maltivariate response variables. It considers the decomposition of the coefficient matrix that leads to the best approximation to the signal part in the response given any rank, and estimates the decomposition by solving a penalized generalized eigenvalue problem followed by a least squares procedure. Ruiyan Luo and Xin Qi (2017) <doi:10.1016/j.jmva.2016.09.005>.

Geometric Density Estimation (RGeode)
Provides the hybrid Bayesian method Geometric Density Estimation. On the one hand, it scales the dimension of our data, on the other it performs inference. The method is fully described in the paper ‘Scalable Geometric Density Estimation’ by Y. Wang, A. Canale, D. Dunson (2016) <http://…/wang16e.pdf>.

Matching Algorithms for Causal Inference with Clustered Data (CMatching)
Provides functions to perform matching algorithms for causal inference with clustered data, as described in B. Arpino and M. Cannas (2016) <doi:10.1002/sim.6880>. Pure within-cluster and preferential-within cluster matching are implemented. Both algorithms provide causal estimates with cluster-adjusted estimates of standard errors.

Surrogate Residuals for Ordinal and General Regression Models (sure)
An implementation of the surrogate approach to residuals and diagnostics for ordinal and general regression models; for details, see Liu and Zhang (2017) <doi:10.1080/01621459.2017.1292915>. These residuals can be used to construct standard residual plots for model diagnostics (e.g., residual-vs-fitted value plots, residual-vs-covariate plots, Q-Q plots, etc.). The package also provides an ‘autoplot’ function for producing standard diagnostic plots using ‘ggplot2’ graphics. The package currently supports cumulative link models from packages ‘MASS’, ‘ordinal’, ‘rms’, and ‘VGAM’. Support for binary regression models using the standard ‘glm’ function is also available.

Multiple Allocation Model for Actor-Event Networks (manet)
Mixture model with overlapping clusters for binary actor-event data. Parameters are estimated in a Bayesian framework. Model and inference are described in Ranciati, Vinciotti, Wit (2017) Modelling actor-event network data via a mixture model under overlapping clusters. Submitted.