Originally as an R version of Preseq <doi:10.1038/nmeth.2375>, the package has extended its functionality to predict the r-species accumulation curve (r-SAC), which is the number of species represented at least r times as a function of the sampling effort. When r = 1, the curve is known as the species accumulation curve, or the library complexity curve in high-throughput genomic sequencing. The package includes both parametric and nonparametric methods, as described by Deng C, et al. (2018) <arXiv:1607.02804v3>.

c(person(given = "Armando",
family = "Lenz",
role = "aut",
email = "armando.lenz@ctu.unibe.ch"),
person(given = "Alan G.",
family = "Haynes",
role = c("cre", "aut"),
email = "alan.haynes@ctu.unibe.ch"),
person(given = "Andreas",
family = "Limacher",
role = "aut",
email = "andreas.limacher@ctu.unibe.ch"),
person(given = "Odile",
family = "Stalder",
role = "ctb",
email = "odile.stalder@ctu.unibe.ch"))
Bland (2009) <doi:10.1136/bmj.b3985> recommended to
base study sizes on the width of the confidence interval rather the power of
a statistical test. The goal of 'presize' is to provide functions for such
precision based sample size calculations. For a given sample size, the
functions will return the precision (width of the confidence interval), and
vice versa.
ggplot2, kappaSize (>= 1.2), shiny, shinydashboard
Armando Lenz [aut],
Alan G. Haynes [cre, aut],
Andreas Limacher [aut],
Odile Stalder [ctb]

binom, ggplot2, Hmisc, testthat, shinydashboard, shinytest

binom, dplyr, ggplot2, gt, Hmisc, knitr, magrittr, markdown,
rmarkdown, shinydashboard, shinytest, testthat, tidyr

Gustavo Soutinho, Luis Meira-Machado and Pedro Oliveira
Provides a function for estimating the transition probabilities in an illness-death model.
The transition probabilities can be estimated from the unsmoothed landmark estimators developed
by de Una-Alvarez and Meira-Machado (2015) <doi:10.1111/biom.12288>.
Presmoothed estimates can also be obtained through the use of a parametric family of binary
regression curves, such as logit, probit or cauchit. The additive logistic regression model
and nonparametric regression are also alternatives which have been implemented.
The idea behind the presmoothed landmark estimators is to use the presmoothing techniques
developed by  Cao et al. (2005) <doi:10.1007/s00180-007-0076-6> in the
landmark estimation of the transition probabilities.