predict.lmcal: Inverse predict concentration from given responses

In quantchem: Quantitative chemical analysis: calibration and evaluation of results

Description

Inverse predict concentration from responses, using all fitted calibration models.

Usage

## S3 method for class 'lmcal'
predict(object, dataset, conf.int = 0.95, ...)
## S3 method for class 'nlscal'
predict(object, dataset, ...)

Arguments

object	an object of class 'lmcal' or 'nlscal', respectively
dataset	a vector of responses
conf.int	confidence intercal (only for lmcal)
...	additional arguments, currently ignored

Details

For linear models, the concentrations are calculated by inverse.predict(), which calls polyroot() on modified polynomial coefficients. For nonlinear models, concentrations are calculated with appropriate 'inverse' formulas.

Value

A list containing following elements. Each element is a list of concentration vectors, calculated from a model, with name referring to the model.

fitted	Concentrations calculated by fitted model
upper	Upper limit of confidence interval of inverse prediction
lower	Lower limit of confidence interval of inverse prediction

Note

The confidence interval for prediction is calculated by taking standard error of prediction and dividing it by slope of calibration curve (estimated by derivative) Then, proper confidence interval is constructed using t statistic.

Author(s)

Lukasz Komsta

See Also

lmcal, nlscal

Examples

set.seed(1234)
x=rep(1:10,10)
y=jitter(sqrt(x))
fit=lmcal(x,y)
predict(fit,rnorm(10,mean=2,sd=0.1))

quantchem documentation built on May 30, 2017, 5:28 a.m.