  In the last decade, developments in tropical geometry have provided a number
of uses directly applicable to problems in statistical learning. The TML
package is the first R package which contains a comprehensive set of tools and
methods used for basic computations related to tropical convexity,
visualization of tropically convex sets, as well as supervised and unsupervised
learning models using the tropical metric under the max-plus algebra over the
tropical projective torus. Primarily, the TML package employs a Hit and Run
Markov chain Monte Carlo sampler in conjunction with the tropical metric as its
main tool for statistical inference. In addition to basic computation and
various applications of the tropical HAR sampler, we also focus on several
supervised and unsupervised methods incorporated in the TML package including
tropical principal component analysis, tropical logistic regression and
tropical kernel density estimation.
