linearQuadraticModel: Fit linear-quadratic curves to dose-response data

In RadioGx: Analysis of Large-Scale Radio-Genomic Data

Description

This function fits a linear-quadratic curve to dose-response data.

Usage

linearQuadraticModel(D, SF, lower_bounds = c(0, 0), upper_bounds = c(1,
  1), scale = 5, family = c("normal", "Cauchy"), median_n = 1,
  trunc = FALSE, verbose = FALSE)

Arguments

D	vector of radiation doses
SF	vector of survival fractions corresponding to the doses
lower_bounds	vector of length 2 containing minimum allowed values of fitted alpha and beta, respectively
upper_bounds	vector of length 2 containing maximum allowed values of fitted alpha and beta, respectively
scale	parameter of the assumed error distribution of the data; see details
family	family of distributions of the error terms in the data; currently supported options are "normal" and "cauchy"
median_n	see details
trunc	should survival fractions be truncated downward to 1? Defaults to FALSE.
verbose	see details

Details

'verbose' outputs warnings that are otherwised suppressed when the function sanity-checks user inputs. 'median_n' denotes the number of distributions from family 'family' that are medianned. (Note that setting n = 1 (the default) is equivalent to using a simple normal or cauchy distribution without taking any medians.)

Examples

linearQuadraticModel(c(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10), 
 c(1.1, 0.8, 0.7, 0.45, 0.15, -0.1, -0.1, -0.4, -0.65, -0.75, -1.1))

RadioGx documentation built on Dec. 20, 2019, 1:06 a.m.