Contains functions for simulating phase 12 trial designs described by Chapple and Thall (2019) including simulation and the EFF-TOX trial and simulation and implementation of the U12 trial. Functions for implementing the EFF-TOX trial are found in the package 'Phase123'.

Predicts a smooth and continuous (individual) utility function from utility points, and computes measures of intensity for risk and higher order risk measures (or any other measure computed with user-written function) based on this utility function and its derivatives according to the method introduced in Schneider (2017) <http://hdl.handle.net/21.11130/00-1735-0000-002E-E306-0>.

The most used functions on IPEA (Instituto de Pesquisa Economica Aplicada). 
             Most of functions deal with brazilian names. 
             It can guess the women single's name, extract prepositions or extract the first name.

Multi-label learning strategies and others procedures to support multi-
  label classification in R. The package provides a set of multi-label procedures such as
  sampling methods, transformation strategies, threshold functions, pre-processing 
  techniques and evaluation metrics. A complete overview of the matter can be seen in
  Zhang, M. and Zhou, Z. (2014) <doi:10.1109/TKDE.2013.39> and Gibaja, E. and 
  Ventura, S. (2015) A Tutorial on Multi-label Learning.

An engine for univariate time series forecasting using
    different regression models in an autoregressive way. The engine
    provides an uniform interface for applying the different models. 
    Furthermore, it is extensible so that users can easily apply their
    own regression models to univariate time series forecasting and 
    benefit from all the features of the engine, such as preprocessings
    or estimation of forecast accuracy.

Tools for generating and handling of UUIDs (Universally Unique Identifiers).

A tool for checking how much information is disclosed when
    reporting summary statistics.

A method for estimating log-normalizing constants (or free
        energies) and expectations from multiple distributions (such as
        multiple generalized ensembles).