Sensitivity Analysis Tools for LSD (LSDsensitivity)
Tools for sensitivity analysis of LSD simulation models. Reads object-oriented data produced by LSD simulation models and performs screening and global sensitivity analysis (Sobol decomposition method, Saltelli et al. (2008) ISBN:9780470725177). A Kriging or polynomial meta-model (Kleijnen (2009) <doi:10.1016/j.ejor.2007.10.013>) is estimated using the simulation data to provide the data required by the Sobol decomposition. LSD (Laboratory for Simulation Development) is free software developed by Marco Valente (documentation and downloads available at <http://labsimdev.org> ).

Rmetrics – Modelling ARMA Time Series Processes (fArma)
Modelling ARMA Time Series Processes.

Load Avro File into ‘Apache Spark’ (sparkavro)
Load Avro Files into ‘Apache Spark’ using ‘sparklyr’. This allows to read files from ‘Apache Avro’ <https://…/>.

Bootstrapping Estimates of Clustering Stability (bootcluster)
Implementation of the bootstrapping approach for the estimation of clustering stability on observation and cluster level, as well as its application in estimating the number of clusters.

Statistical Framework to Define Subgroups in Complex Datasets (Numero)
High-dimensional datasets that do not exhibit a clear intrinsic clustered structure pose a challenge to conventional clustering algorithms. For this reason, we developed an unsupervised framework that helps scientists to better subgroup their datasets based on visual cues [Makinen V-P et al. (2011) J Proteome Res 11:1782-1790, <doi:10.1021/pr201036j>]. The framework includes the necessary functions to import large data files, to construct a self-organizing map of the data, to evaluate the statistical significance of the observed data patterns, and to visualize the results in scalable vector graphics.

Uniform Design of Experiments (UniDOE)
Efficient procedures for constructing uniform design of experiments under various space-filling criteria. It is based on a stochastic and adaptive threshold accepting algorithm with flexible initialization, adaptive threshold, and stochastic evolution. The package may also construct the augmented uniform designs in a sequential manner. View details at: Zhang, A. and Li, H. (2017). UniDOE: An R package for constructing uniform design of experiments via stochastic and adaptive threshold accepting algorithm.