calib {calib}R Documentation

Calibration function

Description

Computes the calibration statistics

Usage

calib(x, y0, conf = 0.9, dilution = 1, samp.names, m = x@m, truth, 
times, samp.units = "", dose.units = "", dose.name = "", 
maxit = 1000, toler = 1e-05, rname = "response", extrap = FALSE, xname = x)

Arguments

x Output from calib.fit.
y0 Points to be calibrated.
conf A vector of mean response values to predict the unknown x.
dilution Dilution factor.
samp.names Names of the unknowns.
m Number of replicates.
truth Optional argument to provide true concentrations if they are known
times ...
samp.units Names of the unknowns
dose.units Units of dose
dose.name Name of dose
maxit Maximum number of iterations to use in optimization
toler Tolerance for optimization step
rname This is the name of the reponse variable
extrap Option to extrapoloate out of range values
xname Names of concentrations

Value

Estimated.x Predicted values of x (for example concentration)
PredStdErr The predicted standard errors of the estimated x's
inver.low The estimate of the lower confidence limit for the predicted x's using inverse estimation
inver.up The estimate of the upper confidence limit for the predicted x's using inverse estimation
wald.low The estimate of the lower confidence limit for the predicted x's using Wald estimation
wald.up The estimate of the upper confidence limit for the predicted x's using Wald estimation
avg.response y0 values

Author(s)

Perry Haaland, Elaine McVey, Daniel Samarov

References

Davidian and Haaland 1990

See Also

calib-class, calib.fit, calib.fit-class, plot

Examples

data(HPLC)
attach(HPLC)
model <- calib.fit(Concentration, Response)
calib(model, Concentration)

[Package calib version 2.0.0 Index]