Directed Weighted Clustering Coefficient (DirectedClustering)
Allows the computation of clustering coefficients for directed and weighted networks by using different approaches. It allows to compute clustering coefficients that are not present in ‘igraph’ package. A description of clustering coefficients can be found in ‘Directed clustering in weighted networks: a new perspective’, Clemente, G.P., Grassi, R. (2017), <doi:10.1016/j.chaos.2017.12.007>.

caret’ Applications for Spatial-Temporal Models (CAST)
Supporting functionality to run ‘caret’ with spatial or spatial-temporal data. ‘caret’ is a frequently used package for model training and prediction using machine learning. This package includes functions to improve spatial-temporal modelling tasks using ‘caret’. It prepares data for Leave-Location-Out and Leave-Time-Out cross-validation which are target-oriented validation strategies for spatial-temporal models. To decrease overfitting and improve model performances, the package implements a forward feature selection that selects suitable predictor variables in view to their contribution to the target-oriented performance.

Process Map Visualization (pmap)
A set of functions to produce the process map visualization for process analysis. It can generate the process map from a process event logs recorded in the process, with the ability of pruning the nodes and/or edges to reduce the complexity of the result.

Person-Oriented Method and Perturbation on the Model (pompom)
An implementation of a hybrid method of person-oriented method and perturbation on the model. Pompom is the initials of the two methods. The hybrid method will provide a multivariate intraindividual variability metric (iRAM). The person-oriented method used in this package refers to uSEM (unified structural equation modeling, see Kim et al., 2007, Gates et al., 2010 and Gates et al., 2012 for details). Perturbation on the model was conducted according to impulse response analysis introduced in Lutkepohl (2007). Kim, J., Zhu, W., Chang, L., Bentler, P. M., & Ernst, T. (2007) <doi:10.1002/hbm.20259>. Gates, K. M., Molenaar, P. C. M., Hillary, F. G., Ram, N., & Rovine, M. J. (2010) <doi:10.1016/j.neuroimage.2009.12.117>. Gates, K. M., & Molenaar, P. C. M. (2012) <doi:10.1016/j.neuroimage.2012.06.026>. Lutkepohl, H. (2007, ISBN:3540262393).

Finding Convergence Clubs (ConvergenceClubs)
Functions for clustering regions that form convergence clubs, according to the definition of Phillips and Sul (2009) <doi:10.1002/jae.1080>.