Advanced ‘tryCatch()’ and ‘try()’ Functions (tryCatchLog)
Advanced tryCatch() and try() functions for better error handling (logging, stack trace with source code references and support for post-mortem analysis).

Dat’ Protocol Interface (datr)
Interface with the ‘Dat’ p2p network protocol <>. Clone archives from the network, share your own files, and install packages from the network.

Sequence Clustering with Discrete-Output HMMs (DBHC)
Provides an implementation of a mixture of hidden Markov models (HMMs) for discrete sequence data in the Discrete Bayesian HMM Clustering (DBHC) algorithm. The DBHC algorithm is an HMM Clustering algorithm that finds a mixture of discrete-output HMMs while using heuristics based on Bayesian Information Criterion (BIC) to search for the optimal number of HMM states and the optimal number of clusters.