Provides basic distribution functions for a mixture model of a Gaussian and exponential distribution.

Initially designed to distribute code for estimating the Gaussian
  graphical model with Lasso regularization, also known as the graphical lasso
  (glasso), using an Expectation-Maximization (EM) algorithm based on work by
  Städler and Bühlmann (2012) <doi:10.1007/s11222-010-9219-7>. As a byproduct,
  code for estimating means and covariances (or the precision matrix) under a
  multivariate normal (Gaussian) distribution is also available.

Simulate and fitting exponential multivariate Hawkes model. 
    This package simulates a multivariate Hawkes model, introduced by Hawkes (1971) <doi:10.2307/2334319>, with an exponential kernel and fits the parameters from the data. 
    Models with the constant parameters, as well as complex dependent structures, can also be simulated and estimated. 
    The estimation is based on the maximum likelihood method, introduced by introduced by Ozaki (1979) <doi:10.1007/BF02480272>, with 'maxLik' package.

A C++ implementation of the following evolutionary
    algorithms: Bat Algorithm (Yang, 2010 <doi:10.1007/978-3-642-12538-6_6>),
    Cuckoo Search (Yang, 2009 <doi:10.1109/nabic.2009.5393690>),
    Genetic Algorithms (Holland, 1992, ISBN:978-0262581110),
    Gravitational Search Algorithm (Rashedi et al., 2009 <doi:10.1016/j.ins.2009.03.004>),
    Grey Wolf Optimization (Mirjalili et al., 2014 <doi:10.1016/j.advengsoft.2013.12.007>),
    Harmony Search (Geem et al., 2001 <doi:10.1177/003754970107600201>),
    Improved Harmony Search (Mahdavi et al., 2007 <doi:10.1016/j.amc.2006.11.033>),
    Moth-flame Optimization (Mirjalili, 2015 <doi:10.1016/j.knosys.2015.07.006>),
    Particle Swarm Optimization (Kennedy et al., 2001 ISBN:1558605959),
    Simulated Annealing (Kirkpatrick et al., 1983 <doi:10.1126/science.220.4598.671>),
    Whale Optimization Algorithm (Mirjalili and Lewis, 2016 <doi:10.1016/j.advengsoft.2016.01.008>).
    'EmiR' can be used not only for unconstrained optimization problems, but also
    in presence of inequality constrains, and variables restricted to be integers.