Title: Estimation and Simulation for PDMPs
Description: This package deals with the estimation of the jump rate for piecewise-deterministic Markov processes (PDMPs), from only one observation of the process within a long time. The main functions provide an estimate of this function. The state space may be discrete or continuous. The associated paper has been published in Scandinavian Journal of Statistics and is given in references. Other functions provide a method to simulate random variables from their (conditional) hazard rate, and then to simulate PDMPs.

Title: Diagnostic Tools and Unit Tests for Statistical Estimators
person("Dmitry", "Otryakhin", email = "d.otryakhin.acad@protonmail.ch", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-4700-7221"))
Author: Dmitry Otryakhin [aut, cre] (<https://orcid.org/0000-0002-4700-7221>)
Description: Extension of 'testthat' package to make unit tests on empirical distributions of estimators and functions for diagnostics of their finite-sample performance.
goftest (>= 1.2-2), testthat (>= 3.0.0), rlang

Suggests: knitr, rmarkdown, doParallel, gridExtra

Title: Perform the Joint Graphical Lasso and Selects Tuning Parameters
Author: Giulio Costantini, Sacha Epskamp
Description: Can be used to simultaneously estimate networks (Gaussian Graphical Models) in data from different groups or classes via Joint Graphical Lasso. Tuning parameters are selected via information criteria (AIC / BIC / eBIC) or crossvalidation.

Author: Giulio Costantini, Nils Kappelmann, Sacha Epskamp
Description: Can be used to simultaneously estimate networks (Gaussian Graphical Models) in data from different groups or classes via Joint Graphical Lasso. Tuning parameters are selected via information criteria (AIC / BIC / extended BIC) or cross validation.
Imports: parallel, igraph, qgraph, dplyr, ggplot2, stats

Title: Maximum Likelihood Estimation for Probability Functions from
Authors@R: person("Jaime", "Mosquera", email = "jmosquerag@unal.edu.co", role = c("aut", "cre"),
Depends: R (>= 3.3.0), stats, DEoptim, boot, numDeriv, BBmisc
Description: A routine for parameter estimation for any probability density or
mass function implemented in R via maximum likelihood (ML) given a data set. This
routine is a wrapper function specifically developed for ML estimation. There are
included optimization procedures such as 'nlminb' and 'optim' from base package,
and 'DEoptim' Mullen (2011) <doi: 10.18637/jss.v040.i06>. Standard errors are
estimated with 'numDeriv' Gilbert (2011) <http://CRAN.R-project.org/package=numDeriv>.
Author: Jaime Mosquera [aut, cre] (<https://orcid.org/0000-0002-1684-4756>)