nCal (version 2021.9-12)

drm.fit: Fit drm

Description

drm.fit fit concentration-response curves using drm function from drc package.

Usage

drm.fit (formula, data, robust="mean", fit.4pl=FALSE, w=NULL, gof.threshold=.2, 
    verbose=FALSE, bcVal = NULL, bcAdd = 0)
# S3 method for drc
getVarComponent (object, ...)

Arguments

formula

a formula object.

data

a data frame object.

robust

a string. Passed to drm. See ?drm for more details.

fit.4pl

boolean. If TRUE, 4PL model is fitted. If FALSE, 5PL model is fitted.

gof.threshold

a threshold to determine when to try more self start functions

w

weights

bcVal

numeric, passed to drm

bcAdd

numeric, passed to drm

...

...

verbose

Boolean. If TRUE, verbose messages are printed.

object

a drm object.

Value

An object of type drm.

Details

drm.fit differs from drc::drm in several aspects.

(1) It tries several self start functions in order to get better fits.

(2) It uses gof.threshold to report lack of fit.

(3) It tried to determine whether the standard deviation of the parameter estimates can be estimated.

Examples

# NOT RUN {
# simulate a dataset
set.seed(1)
log.conc=log(1e4)-log(3)*9:0
n.replicate=2
fi=simulate1curve (p.eotaxin[1,], rep(log.conc,each=n.replicate), sd.e=0.2)
dat.std=data.frame(fi, expected_conc=exp(rep(log.conc,each=n.replicate)), analyte="Test", 
    assay_id="Run 1", sample_id=NA, well_role="Standard", dilution=rep(3**(9:0), each=n.replicate),
    replicate=rep(1:n.replicate, 10))

fit = drm.fit(log(fi) ~ expected_conc, dat = dat.std)
plot(fit, log="xy")
fit

# }