Provides functions for the analysis of
        occupational and environmental data with non-detects. Maximum
        likelihood (ML) methods for censored log-normal data and
        non-parametric methods based on the product limit estimate (PLE)
        for left censored data are used to calculate all of the
        statistics recommended by the American Industrial Hygiene
        Association (AIHA) for the complete data case. Functions for
        the analysis of complete samples using exact methods are also
        provided for the lognormal model. Revised from 2007-11-05
        'survfit~1'.

Tools which allow regression variables to be placed on similar
    scales, offering computational benefits as well as easing interpretation of
    regression output.

Data on standard load profiles from the German Association of 
  Energy and Water Industries (BDEW Bundesverband der Energie- und 
  Wasserwirtschaft e.V.) in a tidy format. The data and methodology are 
  described in VDEW (1999), "Repräsentative VDEW-Lastprofile", 
  <https://www.bdew.de/media/documents/1999_Repraesentative-VDEW-Lastprofile.pdf>.
  The package also offers an interface for generating a standard load profile 
  over a user-defined period. For the algorithm, see VDEW (2000), 
  "Anwendung der Repräsentativen VDEW-Lastprofile step-by-step",
  <https://www.bdew.de/media/documents/2000131_Anwendung-repraesentativen_Lastprofile-Step-by-step.pdf>.

The <http://standartox.uni-landau.de> database offers cleaned,
    harmonized and aggregated ecotoxicological test data, which can
    be used for assessing effects and risks of chemical concentrations
    found in the environment.

Easily create alerts, notifications, modals, info tips and loading 
    screens in 'Shiny'. Includes several options to customize alerts and 
    notifications by including text, icons, images and buttons. When wrapped 
    around a 'Shiny' output, loading screen is automatically displayed while 
    the output is being recalculated.

The C++ header files of the Stan project are provided by this package, but it contains little R code or documentation. The main reference is the vignette. There is a shared object containing part of the 'CVODES' library, but its functionality is not accessible from R. 'StanHeaders' is primarily useful for developers who want to utilize the 'LinkingTo' directive of their package's DESCRIPTION file to build on the Stan library without incurring unnecessary dependencies. The Stan project develops a probabilistic programming language that implements full or approximate Bayesian statistical inference via Markov Chain Monte Carlo or 'variational' methods and implements (optionally penalized) maximum likelihood estimation via optimization. The Stan library includes an advanced automatic differentiation scheme, 'templated' statistical and linear algebra functions that can handle the automatically 'differentiable' scalar types (and doubles, 'ints', etc.), and a parser for the Stan language. The 'rstan' package provides user-facing R functions to parse, compile, test, estimate, and analyze Stan models.