Bound Constrained Optimal Sample Size Allocation
Implements bound constrained optimal sample size allocation (BCOSSA) framework described in Bulus & Dong (2021) <doi:10.1080/00220973.2019.1636197> for power analysis of multilevel regression discontinuity designs (MRDDs) and multilevel randomized trials (MRTs) with continuous outcomes.
Minimum detectable effect size (MDES) and power computations for MRDDs allow polynomial functional form specification for the score variable (with or without interaction with the treatment indicator). See Bulus (2021) <doi:10.1080/19345747.2021.1947425>.

Tools for estimating and predicting the cosinor model
cosinor is a set of simple functions that
transforms longitudinal data to estimate the cosinor
linear model. Methods are given to summarize the mean,
amplitude and acrophase, to predict the mean annual
outcome value, and to test the coefficients.

cosinor is a set of simple functions that transforms longitudinal
data to estimate the cosinor linear model as described in Tong (1976).
Methods are given to summarize the mean, amplitude and acrophase, to
predict the mean annual outcome value, and to test the coefficients.

Tools for Estimating and Predicting the Cosinor Model
A set of simple functions that transforms longitudinal
data to estimate the cosinor linear model as described in Tong (1976).
Methods are given to summarize the mean, amplitude and acrophase, to
predict the mean annual outcome value, and to test the coefficients.

Extended Tools for Cosinor Analysis of Rhythms
Statistical procedures for calculating population–mean cosinor, non–stationary cosinor, estimation of best–fitting period, tests of population rhythm differences and more. See Cornélissen, G. (2014). <doi:10.1186/1742-4682-11-16>.

Mutational Signatures from COSMIC (Catalogue of Somatic
Mutations in Cancer)
c(person(given = "Steven",
family = "Rozen",
role = c("aut", "cre"),
email = "steverozen@pm.me",
comment = c(ORCID = "0000-0002-4288-0056")),
person(given = "Nanhai",
family = "Jiang",
role = "aut",
comment = c(ORCID = "0000-0003-4974-2753")))
A data package with 2 main package variables: 'signature' and 'etiology'.
The 'signature' variable contains the latest mutational signature profiles
released on COSMIC <https://cancer.sanger.ac.uk/signatures/> for 4 mutation
types:
* single base substitutions in the context of preceding and following bases,
* Strand bias single base substitutions: single base substitutions
from transcribed regions, that take into consideration the
the transcribed versus non-transcribed strand,
* Doublet base substitutions, and
* Small insertions and deletions.
The 'etiology' variable provides the known or hypothesized causes of signatures.
'cosmicsig' stands for COSMIC signatures. Please run ?'cosmicsig' for more
information.