calcHillBootstrap {basicdrm}

Estimate Bootstrapped Confidence Intervals on Hill Model Parameters

Description

By bootsttrapping a large number of vectors, this function estimates confidence intervals on the paramters of the given Hill model. If the model already has confidence intervals estimated, they will be replaced with a warning

Usage

calcHillBootstrap(hfit, ciLevs = c(0.025, 0.975), numBoot = NULL)

Arguments

hfit

An object of class hillrm

ciLevs

The lower and upper p-values for the estimated confidence interval. The default values, 0.025 and 0.975, produce a 95% confidence interval.

numBoot

The number of bootstrapped coefficients to be sampled. If NULL (the default) will be selected to have at least 10 samples lie the selected interval, with a minimum of 100 and a maximum of 1000.

Value

An object of class hillrm, containing all the values found in any hillrm object (see fitHillModel()) as well as the following three values:

• ciLevs: the values used to set the bounds of the confidence intervals

• ciCoefs: a width-4 array of all bootstrapped Hill model coefficents sampled by the function

• ciMat: a 2-by-4 array of values representing the estimated confidence intervals on the four Hill model parameters

Examples

conc <- c(0,2^(-6:3),Inf)
hpar <- c(1,3,0,75)
response <- evalHillModel(conc, hpar) + rnorm(length(conc),sd=7.5)

hfit <- fitHillModel(conc,response,c(1,2,3,4),start=c(0.5,1,0,100))
cihfit <- calcHillBootstrap(hfit)