Mónica Bécue-Bertaut, Ramón Alvarez-Esteban, Josep-Anton Sánchez-Espigares, Belchin Kostov

Provides a set of functions devoted to multivariate exploratory statistics on textual data. Classical methods such as correspondence analysis and agglomerative hierarchical clustering are available. Chronologically constrained agglomerative hierarchical clustering enriched with labelled-by-words trees is offered. Given a division of the corpus into parts, their characteristic words and documents are identified. Further, accessing to 'FactoMineR' functions is very easy. Two of them are relevant in textual domain. MFA() addresses multiple lexical table allowing applications such as dealing with multilingual corpora as well as simultaneously analyzing both open-ended and closed questions in surveys. See <http://xplortext.unileon.es> for examples.

Yang and Prentice Model with Baseline Distribution Modeled by
Bernstein Polynomials
person(given = "Fabio", family = "Demarqui", email = "fndemarqui@est.ufmg.br", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-9236-1986"))
Semiparametric modeling of lifetime data with crossing survival curves via Yang and Prentice model with baseline hazard/odds modeled with Bernstein polynomials. Details about the model can be found in Demarqui et al. (2019) <arXiv:1910.04475>. Model fitting can be carried out via both maximum likelihood and Bayesian approaches. The package also provides point and interval estimation for the crossing survival times.
Formula, MASS, methods, Rcpp (>= 0.12.0), rstan (>= 2.18.1),
rstantools (>= 2.0.0)
Fabio Demarqui [aut, cre] (<https://orcid.org/0000-0001-9236-1986>)

Interim Monitoring Using Adaptively Weighted Log-Rank Test in
Clinical Trials
Provide monitoring boundaries for interim testing using the
adaptively weighted log-rank test developed by
Yang and Prentice (2010 <doi:10.1111/j.1541-0420.2009.01243.x>).
The package use a re-sampling method to obtain stopping boundaries
in sequential designs. The output consists of stopping boundaries at
the interim looks along with nominal p-values defined as the
probability of the test exceeding the specific observed value or
critical value, regardless of the test behavior at other looks.
The asymptotic distribution of the test statistics of the adaptively
weighted log-rank test at the interim looks is examined in
Yang (2017, pre-print).