The iterative procedure estimates structural changes in the success probability of Bernoulli variables. It estimates the number and location of the breakpoints as well as the success probability of the different sequences between the breakpoints. In addition, it provides a graphical illustration of the result.

Provides the Augmented Dickey-Fuller test and its variations to check the existence of bubbles (explosive behavior) for time series, based on the article by Peter C. B. Phillips, Shuping Shi and Jun Yu (2015a) <doi:10.1111/iere.12131>. Some functions may take a while depending on the size of the data used, or the number of Monte Carlo replications applied.

Build CPMs (cumulative probability models, also known as cumulative link models) to account for detection limits (both single and multiple detection limits) in response variables. Conditional quantiles and conditional CDFs can be calculated based on fitted models. The package implements methods described in Tian, Y., Li, C., Tu, S., James, N. T., Harrell, F. E., & Shepherd, B. E. (2022). "Addressing Detection Limits with Semiparametric Cumulative Probability Models". <arXiv:2207.02815>.

Fit Cox proportional hazard models with a weighted 
  partial likelihood. It handles one or multiple endpoints, additional matching 
  and makes it possible to reuse controls for other endpoints 
  Stoer NC and Samuelsen SO (2016) <doi:10.32614/rj-2016-030>.

Regression models can be fitted for multiple outcomes simultaneously. This package computes estimates of parameters across fitted models and returns the matrix of asymptotic covariance. Various applications of this package, including CUPED (Controlled Experiments Utilizing Pre-Experiment Data), multiple comparison adjustment, are illustrated.

Tools to analysis of experiments having two or more quantitative explanatory variables and one quantitative dependent variable. Experiments can be without repetitions or with a statistical design (Hair JF, 2016) <ISBN: 13: 978-0138132637>. Pacote para uma analise de experimentos havendo duas ou mais variaveis explicativas quantitativas e uma variavel dependente quantitativa. Os experimentos podem ser sem repeticoes ou com delineamento estatistico (Hair JF, 2016) <ISBN: 13: 978-0138132637>.