fdacluster 0.2.1

Major features

• Add hierarchical clustering;
• Enforce n_clusters in output via linear programming (LP) using the
  lpSolve package;
• New caps class
  for storing results from functional Clustering with Amplitude and
  Phase Separation in a consistent way;
• Add tools for comparing clustering results (mcaps objects, autoplot and
  plot specialized method implementations);
• Add seeding strategies for kmeans (via hierarchical clustering or k-means++ or
  k-means++ with exhaustive search of the first center or exhaustive search of all
  the centers);
• Add within-cluster domain auto-extension via mean imputation;
• Add possibility to cluster according to phase variability instead of amplitude
  variability.
• Add DBSCAN clustering.

Minor improvements

• Fix C++ compiler issues that errored when accessing empty vectors.
• Renaming of functions: to perform k-means with alignment, now use
  fdakmeans(),
  to perform HAC with alignment, now use
  fdahclust().