Harmonic Regression to One or more Time Series
Fits the first harmonics in a Fourier expansion to one or more time series. Trend elimination can be performed.  Computed values include estimates of amplitudes and phases, as well as confidence intervals and p-values for the null hypothesis of Gaussian noise.

Aimed at applying the Harvest classification tree algorithm, which is a modified algorithm of classic classification tree. It was firstly used in drug discovery field, but it also performs well in other kind of data, especially when active region is unrelated.To learn more about the harvest classification algorithm, you can go to http://www.stat.ubc.ca/Research/TechReports/techreports/220.pdf for more information.

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.

Conditional Treatment Effect for Competing Risks
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>.
ahaz, rootSolve, stats, survival, Rdpack (>= 0.7)
Denise Rava [aut, cre, cph],
Ronghui Xu [aut, ths]

Fit Normal or Student-t Heckman Selection Models
c(person("Marcos", "Prates", role=c("aut","cre","trl"),
email="marcosop@est.ufmg.br"),
person("Victor", "Lachos", role="aut"),
person("Dipak", "Dey", role="aut"))
Marcos Prates [aut, cre, trl],
Victor Lachos [aut],
Dipak Dey [aut]
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>.
mvtnorm (>= 1.1-0), sampleSelection (>= 1.2-6), MomTrunc (>=
5.79), PerformanceAnalytics (>= 2.0.4)