Routines for the statistical analysis of landmark shapes, including Procrustes analysis, graphical displays, principal components analysis, permutation and bootstrap tests, thin-plate spline transformation grids and comparing covariance matrices. See Dryden, I.L. and Mardia, K.V. (2016). Statistical shape analysis, with Applications in R (2nd Edition), John Wiley and Sons.

Tool that makes it easier to work with the Terraform Kubernetes Provider converting YAML manifest files to Terraform HCL format.

This library provides a thin, database independent layer over an SQL database. It lacks complex features like schema queries or wrapper classes like active result sets or data bound controls. Instead you get to access the database directly with SQL queries. The library is suited for application programming, not for writing generic database handling tools.

This library provides a thin, database independent layer over an SQL database. It lacks complex features like schema queries or wrapper classes like active result sets or data bound controls. Instead you get to access the database directly with SQL queries. The library is suited for application programming, not for writing generic database handling tools.

Functions to deal with binary classification problems in the presence of imbalanced classes. Synthetic balanced samples are generated according to ROSE (Menardi and Torelli, 2013). Functions that implement more traditional remedies to the class imbalance are also provided, as well as different metrics to evaluate a learner accuracy. These are estimated by holdout, bootstrap or cross-validation methods.

Graphical and computational methods that can be used to assess the stability of results from supervised statistical learning.