testthat, knitr, rmarkdown, viridis, devtools
'GLSZM.R' 'MGLSZM.R' 'GLRLM.R' 'GLCM.R' 'CalculateFeatures.R'
'FirstOrder.R' 'GLCMFeatures.R' 'GLRLMFeatures.R'
'GLSZMFeatures.R' 'ImageQuantize.R' 'RcppExports.R' 'data.R'
'image.R' 'radiomics.R' 'startupMessage.R'

testthat, knitr, rmarkdown, viridis, devtools, roxygen2

Inverse-Regression Estimation of Radioactive Doses
Radioactive doses estimation using individual chromosomal aberrations information. See Higueras M, Puig P, Ainsbury E, Rothkamm K. (2015). A new inverse regression model applied to radiation biodosimetry. Proceedings of the Royal Society A, 471.

David Moriña (Catalan Institute of Oncology), Manuel Higueras (Newcastle University) and Pedro Puig (Universitat Autònoma de Barcelona)
Radioactive doses estimation using individual chromosomal aberrations information. See Higueras M, Puig P, Ainsbury E, Rothkamm K. (2015) <DOI:10.1098/rspa.2014.0588>.

David Moriña (Barcelona Graduate School of Mathematics), Manuel Higueras (Basque Center for Applied Mathematics) and Pedro Puig (Universitat Autònoma de Barcelona)
Radioactive doses estimation using individual chromosomal aberrations information. See Higueras M, Puig P, Ainsbury E, Rothkamm K. (2015) <doi:10.1088/0952-4746/35/3/557>.

Radioactive doses estimation using individual chromosomal aberrations information. See Higueras M, Puig P, Ainsbury E, Rothkamm K. (2015). A new inverse regression model applied to radiation biodosimetry. Proceedings of the Royal Society A, 471

Scientific and technical article format for the web. 'Radix' articles
feature attractive, reader-friendly typography, flexible layout options
for visualizations, and full support for footnotes and citations.
utils, stats, tools, rmarkdown (>= 1.10), htmltools, jsonlite
(>= 1.3), lubridate, png, mime, rstudioapi, rprojroot, xml2,
base64enc, whisker, downloader, progress, stringr, knitr (>=
1.15.6), digest, yaml

Replicability Adjusted p-Values for Two Independent Studies with
Multiple Endpoints
c(
person("Shay", "Yaacoby", email = "shay66@gmail.com", role = "aut"),
person("Marina", "Bogomolov", email = "marinabo@technion.ac.il", role = "aut"),
person("Ruth", "Heller", email = "ruheller@gmail.com", role =  c("aut", "cre")))
Calculates adjusted p-values for the null hypothesis of no replicability
across studies for two study designs: (i) a primary and follow-up study, where the features in the follow-up study
are selected from the primary study, as described in Bogomolov and Heller (2013) <doi:10.1080/01621459.2013.829002> and Heller, Bogomolov and Benjamini (2014) <doi:10.1073/pnas.1314814111>;
(ii) two independent studies, where the features for replicability are first
selected in each study separately, as described in Bogomolov and Heller (2018) <doi:10.1093/biomet/asy029>.
The latter design is the one encountered in a typical meta-analysis of
two studies, but the inference is for replicability rather than for identifying the features that are non-null
in at least one study.
Shay Yaacoby [aut],
Marina Bogomolov [aut],
Ruth Heller [aut, cre]