R Optimization Infrastructure

The R Optimization Infrastructure ('ROI') is a sophisticated framework for handling optimization problems in R. Additional information can be found on the 'ROI' homepage < https://roi.r-forge.r-project.org/>.

Manly Mixture Modeling and Model-Based Clustering

The utility of this package includes finite mixture modeling and model-based clustering through Manly mixture models by Zhu and Melnykov (2016) . It also provides capabilities for forward and backward model selection procedures.

Random Orthonormal Matrix Generation and Optimization on the Stiefel Manifold

Simulation of random orthonormal matrices from linear and quadratic exponential family distributions on the Stiefel manifold. The most general type of distribution covered is the matrix-variate Bingham-von Mises-Fisher distribution. Most of the simulation methods are presented in Hoff(2009) "Simulation of the Matrix Bingham-von Mises-Fisher Distribution, With Applications to Multivariate and Relational Data" . The package also includes functions for optimization on the Stiefel manifold based on algorithms described in Wen and Yin (2013) "A feasible method for optimization with orthogonality constraints" .

Large, Sparse Optimal Matching with Refined Covariate Balance

Tools for large, sparse optimal matching of treated units and control units in observational studies. Provisions are made for refined covariate balance constraints, which include fine and near-fine balance as special cases. Matches are optimal in the sense that they are computed as solutions to network optimization problems rather than greedy algorithms. See Pimentel, et al.(2015) and Pimentel (2016), Obs. Studies 2(1):4-23. The rrelaxiv package, which provides an alternative solver for the underlying network flow problems, carries an academic license and is not available on CRAN, but may be downloaded from Github at < https://github.com/josherrickson/rrelaxiv/>.

Animal Network Toolkit Software

How animals interact and develop social relationships in face of sociodemographic and ecological pressures is of great interest. New methodologies, in particular Social Network Analysis (SNA), allow us to elucidate these types of questions. However, the different methodologies developed to that end and the speed at which they emerge make their use difficult. Moreover, the lack of communication between the different software developed to provide an answer to the same/different research questions is a source of confusion. The R package Animal Network Toolkit 'ANTs' was developed with the aim of implementing in one package the different social network analysis techniques currently used in the study of animal social networks. Hence, ANT is a toolkit for animal research allowing among other things to: 1) measure global, dyadic and nodal networks metrics; 2) perform data randomization: pre- and post-network (node and link permutations); 3) perform statistical permutation tests as correlation test (), t-test (), General Linear Model (), General Linear Mixed Model (), deletion simulation (), 'Matrix TauKr correlations' (). The package is partially coded in C++ using the R package 'Rcpp' for an optimal coding speed. The package gives researchers a workflow from the raw data to the achievement of statistical analyses, allowing for a multilevel approach (): from the individual's position and role within the network, to the identification of interaction patterns, and the study of the overall network properties. Furthermore, ANT also provides a guideline on the SNA techniques used: 1) from the appropriate randomization technique according to the data collected; 2) to the choice, the meaning, the limitations and advantages of the network metrics to apply, 3) and the type of statistical tests to run. The ANT project is multi-collaborative, aiming to provide access to advanced social network analysis techniques and to create new ones that meet researchers' needs in future versions. The ANT project is multi-collaborative, aiming to provide access to advanced social network analysis techniques and to create new ones that meet researchers' needs in future versions.

'ECOS' Plugin for the 'R' Optimization Infrastructure

Enhances the 'R' Optimization Infrastructure ('ROI') package with the Embedded Conic Solver ('ECOS') for solving conic optimization problems.

'Rcpp' Integration for Numerical Computing Libraries

A collection of open source libraries for numerical computing (numerical integration, optimization, etc.) and their integration with 'Rcpp'.

Constrained Nonlinear Optimization

Augmented Lagrangian Adaptive Barrier Minimization Algorithm for optimizing smooth nonlinear objective functions with constraints. Linear or nonlinear equality and inequality constraints are allowed.

An Alternative Advanced Normalization Tools ('ANTs')

Provides portable access from 'R' to biomedical image processing toolbox 'ANTs' by Avants et al. (2009) via seamless integration with the 'Python' implementation 'ANTsPy'. Allows biomedical images to be processed in 'Python' and analyzed in 'R', and vice versa via shared memory. See 'citation("rpyANTs")' for more reference information.

Genetic Tools for Colony Management

Provides genetic tools for colony management and is a derivation of the work in Amanda Vinson and Michael J Raboin (2015) < https://pmc.ncbi.nlm.nih.gov/articles/PMC4671785/> "A Practical Approach for Designing Breeding Groups to Maximize Genetic Diversity in a Large Colony of Captive Rhesus Macaques ('Macaca' 'mulatto')". It provides a 'Shiny' application with an exposed API. The application supports five groups of functions: (1) Quality control of studbooks contained in text files or 'Excel' workbooks and of pedigrees within 'LabKey' Electronic Health Records (EHR); (2) Creation of pedigrees from a list of animals using the 'LabKey' EHR integration; (3) Creation and display of an age by sex pyramid plot of the living animals within the designated pedigree; (4) Generation of genetic value analysis reports; and (5) Creation of potential breeding groups with and without proscribed sex ratios and defined maximum kinships.