Supervised Cluster Analysis (supcluster)
Clusters features under the assumption that each cluster has a random effect and there is an outcome variable that is related to the random effects by a linear regression. In this way the cluster analysis is ‘supervised’ by the outcome variable. An alternate specification is that features in each cluster have the same compound symmetric normal distribution, and the conditional distribution of the outcome given the features has the same coefficient for each feature in a cluster.

NOVEL Integration of the Sample and Thresholded (NOVELIST) Correlation and Covariance Estimators (novelist)
Estimate Large correlation and covariance matrices and their inverses using integration of the sample and thresholded correlation and covariance estimators.

Single- and Multi-Objective Optimization Functions (smoof)
This package offers an interface for objective functions in the context of (multi-objective) global optimization. It conveniently builds up on the S3 objects, i. e., an objective function is a S3 object composed of a descriptive name, the function itself, a parameter set, box constraints or other constraints, number of objectives and so on. Moreover, the package contains generators for a load of both single- and multi-objective optimization test functions which are frequently being used in the literature of (benchmarking) optimization algorithms. The bi-objective ZDT function family by Zitzler, Deb and Thiele is included as well as the popular single-objective test functions like De Jong’s function, Himmelblau function and Schwefel function. Moreover, the package offers a R interface to the C implementation of the Black-Box Optimization Benchmarking (BBOB) set of noiseless test functions.