Bayesian solutions to biodosimetry count data problems and supporting software

Manuel Higueras; Elizabeth Ainsbury

doi:10.1007/978-3-319-55639-0_17

Bayesian solutions to biodosimetry count data problems and supporting software

Manuel Higueras^*
, Elizabeth Ainsbury

^*Corresponding author for this work

Radiation Effects

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

1 Citation (Scopus)

Abstract

Recently developed Bayesian models for the estimation of the absorbed ionising radiation dose in whole and partial body homogenous exposures are introduced. The whole body exposure models can manage with overdispersed frequencies of chromosomal aberrations. Poisson models have been implemented in the R package radir.

Original language	English
Title of host publication	Trends in Mathematics
Publisher	Springer International Publishing
Pages	103-107
Number of pages	5
DOIs	https://doi.org/10.1007/978-3-319-55639-0_17
Publication status	Published - 2017

Publication series

Name	Trends in Mathematics
Volume	7
ISSN (Print)	2297-0215
ISSN (Electronic)	2297-024X

Bibliographical note

Publisher Copyright:
© 2017, Springer International Publishing AG.

Access to Document

10.1007/978-3-319-55639-0_17

Cite this

@inbook{a7a28af70dc542e593595a3ad1c5383e,

title = "Bayesian solutions to biodosimetry count data problems and supporting software",

abstract = "Recently developed Bayesian models for the estimation of the absorbed ionising radiation dose in whole and partial body homogenous exposures are introduced. The whole body exposure models can manage with overdispersed frequencies of chromosomal aberrations. Poisson models have been implemented in the R package radir.",

author = "Manuel Higueras and Elizabeth Ainsbury",

note = "Publisher Copyright: {\textcopyright} 2017, Springer International Publishing AG.",

year = "2017",

doi = "10.1007/978-3-319-55639-0\_17",

language = "English",

series = "Trends in Mathematics",

publisher = "Springer International Publishing",

pages = "103--107",

booktitle = "Trends in Mathematics",

}

TY - CHAP

T1 - Bayesian solutions to biodosimetry count data problems and supporting software

AU - Higueras, Manuel

AU - Ainsbury, Elizabeth

PY - 2017

Y1 - 2017

N2 - Recently developed Bayesian models for the estimation of the absorbed ionising radiation dose in whole and partial body homogenous exposures are introduced. The whole body exposure models can manage with overdispersed frequencies of chromosomal aberrations. Poisson models have been implemented in the R package radir.

AB - Recently developed Bayesian models for the estimation of the absorbed ionising radiation dose in whole and partial body homogenous exposures are introduced. The whole body exposure models can manage with overdispersed frequencies of chromosomal aberrations. Poisson models have been implemented in the R package radir.

UR - https://www.scopus.com/pages/publications/85019133769

U2 - 10.1007/978-3-319-55639-0_17

DO - 10.1007/978-3-319-55639-0_17

M3 - Chapter

AN - SCOPUS:85019133769

T3 - Trends in Mathematics

SP - 103

EP - 107

BT - Trends in Mathematics

PB - Springer International Publishing

ER -

Bayesian solutions to biodosimetry count data problems and supporting software

Abstract

Publication series

Bibliographical note

Access to Document

Other files and links

Fingerprint

Cite this