Calculates the optimal price of assets (such as
	airline flight seats, hotel room bookings) whose value
	becomes zero after a fixed ``expiry date''.  Assumes
	potential customers arrive (possibly in groups) according
	to a known inhomogeneous Poisson process.  Also assumes a
	known time-varying elasticity of demand (price sensitivity)
	function.  Uses elementary techniques based on ordinary
	differential equations.  Uses the package deSolve to effect
	the solution of these differential equations.

Use Monte-Carlo and K-fold cross-validation coupled with machine-
    learning classification algorithms to perform population assignment, with
    functionalities of evaluating discriminatory power of independent training
    samples, identifying informative loci, reducing data dimensionality for genomic
    data, integrating genetic and non-genetic data, and visualizing results.

Routines for re-scaling isotope maps using known-origin tissue isotope data, assigning origin of unknown samples, and summarizing and assessing assignment results. Methods are adapted from Wunder (2010, in ISBN:9789048133536) and Vander Zanden, H. B. et al. (2014) <doi:10.1111/2041-210X.12229> as described in Ma, C. et al. (2020) <doi:10.1111/2041-210X.13426>.

Fit various smoothing spline models. Includes an ssr() function for smoothing 
    spline regression, an nnr() function for nonparametric nonlinear regression, an snr() 
    function for semiparametric nonlinear regression, an slm() function for semiparametric 
    linear mixed-effects models, and an snm() function for semiparametric nonlinear 
    mixed-effects models. See Wang (2011) <doi:10.1201/b10954> for an overview.

Clinical trial design for subgroup selection in three-stage group
             sequential trial as described in Lai, Lavori and Liao (2014,
	     <doi:10.1016/j.cct.2014.09.001>). Includes facilities for design,
	     exploration and analysis of such trials. An implementation of
	     the initial DEFUSE-3 trial is also provided as a vignette.