Set of tools to compute metrics and indices for climate analysis.
    The package provides functions to compute extreme indices, evaluate the
    agreement between models and combine theses models into an ensemble. Multi-model
    time series of climate indices can be computed either after averaging the 2-D
    fields from different models provided they share a common grid or by combining
    time series computed on the model native grid. Indices can be assigned weights
    and/or combined to construct new indices. The package makes use of some of the
    methods described in:
    N. Manubens et al. (2018) <doi:10.1016/j.envsoft.2018.01.018>.

Contains functions to detect and visualise periods of climate
    sensitivity (climate windows) for a given biological response. 
    Please see van de Pol et al. (2016) <doi:10.1111/2041-210X.12590> 
    and Bailey and van de Pol (2016) <doi:10.1371/journal.pone.0167980> for details.

Creation of interactive tables, listings and figures ('TLFs') 
  and associated report for exploratory analysis of data in a clinical trial, 
  e.g. for clinical oversight activities.
  Interactive figures include sunburst, treemap, scatterplot, line plot and
  barplot of counts data. 
  Interactive tables include table of summary statistics
  (as counts of adverse events, enrollment table) and listings.
  Possibility to compare data (summary table or listing) across two data batches/sets.
  A clinical data review report is created via study-specific configuration 
  files and template 'R Markdown' reports contained in the package.

Bayesian and ML Emax model fitting, graphics and simulation for clinical dose
    response.  The summary data from the dose response meta-analyses in  
    Thomas, Sweeney, and Somayaji (2014) <doi:10.1080/19466315.2014.924876> and
    Thomas and Roy (2016) <doi:10.1080/19466315.2016.1256229> 
    Wu, Banerjee, Jin, Menon, Martin, and Heatherington(2017) <doi:10.1177/0962280216684528> 
    are included 
    in the package.  The prior distributions for the Bayesian analyses default to
    the posterior predictive distributions derived from these references.