A tidy framework for automatic knowledge classification and visualization. Currently, the core functionality of the framework is mainly supported by modularity-based clustering (community detection) in keyword co-occurrence network, and focuses on co-word analysis of bibliometric research. However, the designed functions in 'akc' are general, and could be extended to solve other tasks in text mining as well.

Continuous and discrete (count or categorical) estimation of density, probability mass function (p.m.f.) and regression functions are performed using associated kernels. The cross-validation technique and the local Bayesian procedure are also implemented for bandwidth selection.

Flagger to detect acute kidney injury (AKI) in a patient dataset.

Several cubic spline interpolation methods of H. Akima for irregular and
  regular gridded data are available through this package, both for the bivariate case
  (irregular data: ACM 761, regular data: ACM 760) and univariate case (ACM 433 and ACM 697).
  Linear interpolation of irregular gridded data is also covered by reusing D. J. Renkas
  triangulation code which is part of Akimas Fortran code. A bilinear interpolator
  for regular grids was also added for comparison with the bicubic interpolator on
  regular grids.
  Please note that most of the functions are now also covered in package
  interp, which is a re-implementation from scratch under a free license.

Implements the alternating k-means biclustering algorithm in Fraiman and Li (2020) <arXiv:2009.04550>.

Augmented Lagrangian Adaptive Barrier Minimization
        Algorithm for optimizing smooth nonlinear objective functions
        with constraints. Linear or nonlinear equality and inequality
        constraints are allowed.

Provides methods for high-throughput adaptive immune 
    receptor repertoire sequencing (AIRR-Seq; Rep-Seq) analysis. In 
    particular, immunoglobulin (Ig) sequence lineage reconstruction, 
    lineage topology analysis, diversity profiling, amino acid property 
    analysis and gene usage.
    Citations: 
    Gupta and Vander Heiden, et al (2017) <doi:10.1093/bioinformatics/btv359>,
    Stern, Yaari and Vander Heiden, et al (2014) <doi:10.1126/scitranslmed.3008879>.