Bindings to edlib, a lightweight performant C/C++ library for exact pairwise sequence alignment using edit distance (Levenshtein distance). The algorithm computes the optimal alignment path, but also can be used to find only the start and/or end of the alignment path for convenience. Edlib was designed to be ultrafast and require little memory, with the capability to handle very large sequences. Three alignment methods are supported: global (Needleman-Wunsch), infix (Hybrid Wunsch), and prefix (Semi-Hybrid Wunsch). The original C/C++ library is described in "Edlib: a C/C++ library for fast, exact sequence alignment using edit distance", M. Šošić, M. Šikić, <doi:10.1093/bioinformatics/btw753>.

Perform dynamic model averaging with grid search as in Dangl and Halling (2012) <doi:10.1016/j.jfineco.2012.04.003> using parallel computing.

Implements various general algorithms to estimate missing elements
   of a Euclidean (squared) distance matrix.  
   Includes optimization methods based on semi-definite programming found in
   Alfakih, Khadani, and Wolkowicz (1999)<doi:10.1023/A:1008655427845>, 
   a non-convex position formulation by Fang and O'Leary (2012)<doi:10.1080/10556788.2011.643888>, and 
   a dissimilarity parameterization formulation by Trosset (2000)<doi:10.1023/A:1008722907820>.
   When the only non-missing
   distances are those on the minimal spanning tree, the guided random search
   algorithm will complete the matrix while preserving the minimal spanning tree following
   Rahman and Oldford (2018)<doi:10.1137/16M1092350>.
   Point configurations in specified dimensions can be determined from the completions. 
   Special problems such as the sensor localization problem, 
   as for example in Krislock and Wolkowicz (2010)<doi:10.1137/090759392>,
   as well as reconstructing
   the geometry of a molecular structure, as for example in 
   Hendrickson (1995)<doi:10.1137/0805040>, can also be solved.
   These and other methods are described in the thesis of Adam Rahman(2018)<https://hdl.handle.net/10012/13365>.