| radir-package {radir} | R Documentation |
Inverse regression model for radiation biodosimetry
Description
The package implements a new inverse regression model with applications to radiation biodosimetry.
Details
| Package: | radir |
| Type: | Package |
| Version: | 1.0.4 |
| Date: | 2019-6-30 |
| License: | GPL version 2 or newer |
| LazyLoad: | yes |
The package implements a new inverse regression model with applications to radiation biodosimetry by means of the function dose.distr. It allows for several distributions for the dose prior including uniform and gamma, and for the mean prior, including gamma and normal distributions. A summary containing the most relevant information about the estimated doses can be obtained via summary and graphics can be obtained in a standard way by means of plot or lines functions.
Author(s)
David Moriña (Barcelona Graduate School of Mathematics), Manuel Higueras (Basque Center for Applied Mathematics) and Pedro Puig (Universitat Autònoma de Barcelona)
Mantainer: David Moriña Soler <david.morina@uab.cat>
References
Higueras M, Puig P, Ainsbury EA, Rothkamm K. A new inverse regression model applied to radiation biodosimetry. Proc R Soc A 2015;471, http://dx.doi.org/10.1098/rspa.2014.0588
See Also
Examples
f <- expression(b1*x+b2*x^2)
pars <- c("b1","b2")
beta <- c(3.126e-3, 2.537e-2)
cov <- matrix(c(7.205e-06,-3.438e-06,-3.438e-06,2.718e-06),nrow=2)
ex1.a <- dose.distr(f, pars, beta, cov, cells=1811, dics=102,
m.prior="normal", d.prior="uniform", prior.param=c(0, Inf))
summary(ex1.a)
plot(ex1.a)