c(person(given = "Harry",
family = "Smith",
role = c("aut", "cre"),
email = "harry.smith@ucdenver.edu"),
person(given = "Laura",
family = "Saba",
role = "aut",
email = "laura.saba@ucdenver.edu"))

Functions from the book Solving Differential Equations in R
R (>= 2.01), deSolve, rootSolve, bvpSolve, ReacTran, deTestSet
Functions and examples from the book Solving Differential
Equations in R by Karline Soetaert, Jeff R Cash and Francesca Mazzia.
Springer, 2012.

R (>= 2.01), deSolve, rootSolve, bvpSolve, ReacTran, diagram,
deTestSet, scatterplot3d
Functions and examples from the book Solving Differential
Equations in R by Karline Soetaert, Jeff R Cash and Francesca
Mazzia.  Springer, 2012.

Diffusion-based IRT models for Response and Response Time Data
Package to fit diffusion-based IRT models to response and
response time data. Models are fitted using marginal maximum
likelihood. Parameter restrictions (fixed value and equality
constraints) are possible. In addition, factor scores (person drift
rate and person boundary separation) can be estimated. Model fit
assessment tools are also available. The traditional diffusion model
can be estimated as well.

Diffusion IRT models for Response and Response Time Data

Diffusion IRT Models for Response and Response Time Data
Package to fit diffusion-based IRT models to response and
response time data. Models are fit using marginal maximum
likelihood. Parameter restrictions (fixed value and equality
constraints) are possible. In addition, factor scores (person drift
rate and person boundary separation) can be estimated. Model fit
assessment tools are also available. The traditional diffusion model
can be estimated as well.

Detecting Gene Probes with Different Means or Variances Between
Two Groups
c(person("Xuan", "Li", role=c("aut", "ctb"),
email = "lixuan0759@gmail.com"),
person("Weiliang", "Qiu", role=c("aut", "cre"),
email = "stwxq@channing.harvard.edu"),
person("Yuejiao", "Fu", role = c("aut", "ctb"),
email = "yuejiao@mathstat.yorku.ca"),
person("Xiaogang", "Wang", role = c("aut", "ctb"),
email = "stevenw@mathstat.yorku.ca")
)
Xuan Li [aut, ctb],
Weiliang Qiu [aut, cre],
Yuejiao Fu [aut, ctb],
Xiaogang Wang [aut, ctb]
R (>= 3.4.0), Biobase, missMethyl, stats
MASS, graphics, lawstat, methylumi, grDevices
A collection of functions to detect gene probes with different means or variances between two groups in (epi)-genomic data analysis, including classical F test and Levene's test for equal variance, likelihood ratio test for equal mean and equal variance, the wrappers for functions in R Bioconductor package 'missMethyl' (Phipson and Oshlack (2014) <doi:10.1186/s13059-014-0465-4>), the implementation of the methods proposed by Ahn and Wang (2013) <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3621641/>, and the improved Ahn and Wang's methods that we proposed recently (Qiu and Li et al. (2017) <http://oprscience.com/wp-content/uploads/2016/07/new-score-tests-for-equality-of-variances-in-the-application-of-dna-methylation-data-analysis.pdf>).