Measures the degree of balance for a given phylogenetic tree by 
  calculating the Total Cophenetic Index.
  Reference: A. Mir, F. Rossello, L. A. Rotger (2013).
  A new balance index for phylogenetic trees.
  Math. Biosci. 241, 125-136 <doi:10.1016/j.mbs.2012.10.005>.

Estimates the parameters of a Transformed Ornstein-Uhlenbeck (TOU) stochastic model for adsorption data and also the parameters of the related pseudo-n-order (PNO) model, such as the maximum adsorption capacity (qe), the adsorption rate constant (kn) and the order of the model (n).

R implementation of the software tools developed in the H-CUP
    (Healthcare Cost and Utilization Project) <https://www.hcup-us.ahrq.gov>
    and AHRQ (Agency for Healthcare Research and Quality)
    <https://www.ahrq.gov>.  It currently contains functions for mapping ICD-9
    codes to the AHRQ comorbidity measures and translating ICD-9
    (resp. ICD-10) codes to ICD-10 (resp. ICD-9) codes based on GEM (General
    Equivalence Mappings) from CMS (Centers for Medicare and Medicaid
    Services).

Several datasets which describe the challenges and results of
    competitions in Tournament of Champions.  This data is useful for
    practicing data wrangling, graphing, and analyzing how each season of
    Tournament of Champions played out.

Implements geodesic interpolation and basis
    generation functions that allow you to create new tour
    methods from R.

Non-imputational method for handling missing values in 
   a prediction context, meaning that not only are there missing
   values in the training dataset, but also some values may be missing
   in future cases to be predicted. Based on the notion of regression
   averaging (Matloff (2017, ISBN: 9781498710916)).

Computation of stopping boundaries for a single-arm trial using a
    Bayesian criterion; i.e., for each m<=n (n= total patient number of the 
    trial) the smallest number of observed toxicities is calculated
    leading to the termination of the trial/accrual according to the specified 
    criteria. The probabilities of stopping the trial/accrual at and up until 
    (resp.) the m-th patient (m<=n) is also calculated. This design is more 
    conservative than the frequentist approach (using Clopper Pearson CIs)
    which might be preferred as it concerns safety.See also Aamot et.al.(2010) 
    "Continuous monitoring of toxicity in clinical trials - simulating the risk 
    of stopping prematurely" <doi:10.5414/cpp48476>.