Description: Provides tools to assess the dissimilarity between multivariate time-series. It is based on the psi measure described  by Birks and Gordon (1985 <doi:10.1002/jqs.3390020110>), which computes dissimilarity between irregular time-series constrained by sample order. However, in this package the original idea has been extended to work with any kind of multivariate time-series, no matter whether they are regular, irregular, aligned or unaligned. Furthermore, the package allows to assess the significance of dissimilarity values by applying a restricted permutation test, allows to measure the contribution of individual variables to dissimilarity, and offers tools to transfer attributes (generally time or age, but other are possible) between sequences based on the similarity of their samples.
viridis, RColorBrewer, data.table, iterators, arrangements

Title: Computations over Distributed Data without Aggregation
Imports: utils, shiny, httr, digest, jsonlite, stringr, R6 (>= 2.0)
Description: Implementing algorithms and fitting models when sites (possibly remote) share
computation summaries rather than actual data over HTTP with a master R process (using
'opencpu', for example). A stratified Cox model and a singular value decomposition are
provided. The former makes direct use of code from the R 'survival' package. (That is,
the underlying Cox model code is derived from that in the R 'survival' package.)
Sites may provide data via several means: CSV files, Redcap API, etc. An extensible
design allows for new methods to be added in the future. Web applications are provided
(via 'shiny') for the implemented methods to help in designing and deploying the
Author: Balasubramanian Narasimhan [aut, cre], Marina Bendersky [aut],
Sam Gross [aut], Terry M. Therneau [ctb], Thomas Lumley [ctb]

Imports: utils, shiny, httr (>= 1.0.0), digest, jsonlite, stringr, R6

design allows for new methods to be added in the future and includes facilities
for local prototyping and testing. Web applications are provided (via 'shiny') for
the implemented methods to help in designing and deploying the computations.