Description: Aimed at applying the Harvest classification tree algorithm, modified algorithm of classic classification tree.The harvested tree has advantage of deleting redundant rules in trees, leading to a simplify and more efficient tree model.It was firstly used in drug discovery field, but it also performs well in other kinds of data, especially when the region of a class is disconnected. This package also improves the basic harvest classification tree algorithm by extending the field of data of algorithm to both continuous and categorical variables. To learn more about the harvest classification tree algorithm, you can go to http://www.stat.ubc.ca/Research/TechReports/techreports/220.pdf for more information.

Title: Conditional Treatment Effect for Competing Risks
Description: The conditional treatment effect for competing risks data in observational studies is estimated. While it is described as a constant difference between the hazard functions given the covariates, we do not assume specific functional forms for the covariates. Rava, D. and Xu, R. (2021) <arXiv:2112.09535>.
Imports: ahaz, rootSolve, stats, survival, Rdpack (>= 0.7)

Title: Fit Normal or Student-t Heckman Selection Models
Description: Maximum likelihood estimation by an EM algorithm of Heckman-type sample selection Normal or Student-t models. The reference is Lachos, Prates and Dey (2020) <arXiv:2006.08036>.
Imports: mvtnorm (>= 1.1-0), sampleSelection (>= 1.2-6), MomTrunc (>=

Description: Maximum likelihood estimation by an EM algorithm of Heckman-type sample selection Normal or Student-t models. The reference is Lachos, Prates and Dey (2020) <doi:10.1016/j.jmva.2021.104737>.

Authors@R: c(person("Gery", "Geenens", role = c("aut"),
Description: Empirical value of the Hellinger correlation, which is a new measure of dependence between
two continuous random variables that satisfies a set of 7 axioms that
any valid measure of dependence should satisfy. More details can be found in Geenens and Lafaye De Micheaux (2018) <arXiv:1810.10276>.