summary.lmcal, summary.nlscal {quantchem}R Documentation

Summarizing fitted calibration curves

Description

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

Usage

summary.lmcal(object, sort.models = FALSE, ...)
summary.nlscal(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.

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.

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

Note

The p-value of Durbin-Watson statistic is *only* approximated using normal transform algorhitm! This is not critical criterion and *always* residual plot should be visually examined.

Some of values given above are not computed for 'nlscal' models.

Author(s)

Lukasz Komsta, with portion by Achim Zeileis (from dwtest())

See Also

lmcal, nlscal

Examples

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

[Package quantchem version 0.12-1 Index]