# summary.lmcal, summary.nlscal: Summarizing fitted calibration curves

## Description

A 'summary' class for 'lmcal' and 'nlscal' objects.

## Usage

"summary"(object, sort.models = FALSE, ...)
"summary"(object, sort.models = FALSE, ...)

## Arguments

object

an object of class 'lmcal' or 'nlscal'

sort.models

should the tables be sorted by models (TRUE) or variables (FALSE).

...

additional arguments, currently ignored.

## Value

A list, consisting of following items:- coefficients
- Estimated coefficients, their standard error, significance (t) and p-value
- residuals
- Quantiles of residuals and Shapiro-Wilk test of their normality
- variances
- Quantiles of variances (without transform, with log-log, and with Box-Cox on y)
ond Bartlett test for therir heteroscedascity. Calculated only, if there are at least
2 replicates for each x
- fit
- R-squared, adjusted R-squared, AIC, residual standard error, sum of squared residuals,
sum of pure error and Lack-of-Fit ANOVA test
- sensitivity
- sensitivity, limit of detection and quantitation, autocorrelation of residuals,
Durbin-Watson test for autocorrelation

## Details

The function performs summarizing of fitted calibration models and produces several
tables (see below). The are printed in appropriate form, and their list is returned
invisibly.

## Examples

set.seed(1234)
x=rep(1:8,5)
y=jitter(sqrt(x))
fit=lmcal(x,y)
fit
summary(fit)