linearQuadraticModel {RadioGx} | R Documentation

## Fit linear-quadratic curves to dose-response 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 sdetails
`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` | '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.)

### Value

`numeric` The estimated alpha and beta values

### 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))

[Package RadioGx version 1.4.0 Index]