Tools to compute depth measures and implementations of related 
             tasks such as outlier detection, data exploration and 
            classification of multivariate, regression and functional data.

Three algorithms for estimating a Markov random field structure.Two of them are an exact version and a simulated annealing version of a penalized maximum conditional likelihood method similar to the Bayesian Information Criterion. These algorithm are described in Frondana (2016) <doi:10.11606/T.45.2018.tde-02022018-151123>.The third one is a greedy algorithm, described in Bresler (2015) <doi:10.1145/2746539.2746631).

Simulation from an 'mrgsolve' 
    <https://cran.r-project.org/package=mrgsolve> model using a parallel backend.  
    Input data sets are split (chunked) and simulated in parallel using 
    mclapply() or future_lapply() 
    <https://cran.r-project.org/package=future.apply>.

Perform sensitivity analysis on ordinary differential equation 
    based models, including ad-hoc graphical analyses based on structured 
    sequences of parameters as well as local sensitivity analysis. Functions 
    are provided for creating inputs, simulating scenarios and plotting outputs.

Fast simulation from ordinary differential equation
    (ODE) based models typically employed in quantitative pharmacology and
    systems biology.

Simulate a (bivariate) multivariate renewal Hawkes (MRHawkes) 
    self-exciting process, with given immigrant hazard rate functions and 
    offspring density function. Calculate the likelihood of a MRHawkes process 
    with given hazard rate functions and offspring density function for an 
    (increasing) sequence of event times. Calculate the Rosenblatt residuals of the 
    event times. Predict future event times based on observed event times up to a 
    given time. For details see Stindl and Chen (2018) <doi:10.1016/j.csda.2018.01.021>.

It provides functions to compute the values of different modifications of the Rand and Wallace indices. The indices are used to measure the stability or similarity of two partitions obtained on two different sets of units with a non-empty intercept. Splitting and merging of clusters can (depends on the selected index) have a different effect on the value of the indices.  The indices are proposed in Cugmas and Ferligoj (2018) <http://ibmi.mf.uni-lj.si/mz/2018/no-1/Cugmas2018.pdf>.