Graphical Markov models (GMM) use graphs, either undirected, directed, or mixed, to represent multivariate dependences in a visual and computationally efficient manner. The following are Functions for analyzing and fitting Graphical Markov models.
3D printing is a process of making a three-dimensional solid object of virtually any shape from a digital model. This package is used for visualizing data using a 3D printer Package r2stl converts R data to STL (stereolithography) files that can be used to feed a 3-dimensional printer
a generalized additive model (GAM) is a generalized linear model in which the linear predictor depends linearly on unknown smooth functions of some predictor variables, and interest focuses on inference about these smooth functions. The following package is about Robust Generalized Additive Model.
Canonical correlation analysis is a popular statistical method for the study of the correlations between two sets of variables. This package implements the functions associated with Fast Regularized Canonical Correlation Analysis.
This package used to develop a core collection for biological resources like genbanks. A core collection is defined as a sample of accessions that represent, with the lowest possible level of redundancy, the genetic diversity (the richness of gene or genotype categories) of the entire collection.