Deals with many computations related to the thermodynamics of atmospheric processes. It includes many functions designed to consider the density of air with varying degrees of water vapour in it, saturation pressures and mixing ratios, conversion of moisture indices, computation of atmospheric states of parcels subject to dry or pseudoadiabatic vertical evolutions and atmospheric instability indices that are routinely used for operational weather forecasts or meteorological diagnostics.

Nonparametric estimation of additive isotonic covariate effects for proportional hazards model.

Uncertainty quantification and inverse estimation by probabilistic generative models  from the beginning of the data analysis. An example is a Fourier basis method for inverse estimation in scattering analysis of microscopy videos. It does not require specifying a certain range of Fourier bases and it substantially reduces computational cost via the generalized Schur algorithm. See the reference: Mengyang Gu, Yue He, Xubo Liu and Yimin Luo (2023), <arXiv:2309.02468>.

A thin wrapper around the 'ajv' JSON validation package for
    JavaScript. See <http://epoberezkin.github.io/ajv/> for details.

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.