lof: Lack-of-Fit testing of calibration models

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

Description

Performs 'a priori' ANOVA "Lack-of-Fit" tests on fitted calibration models.

Usage

lof(obj)

Arguments

obj	An object inheriting from 'cal' (fitted by 'lmcal' or 'nlscal')

Details

This function performs lack-of-fit test on regression residuals. This test assumes, that overall residual error should not be significantly larger than error within groups with the same x (replicates). It is called by 'summary' methods, but also can be called directly by user.

Value

A matrix containing sum of squared residuals, sum of pure error, F-statistic and corresponding p-value.

Note

This test is possible to perform only with minimum 2 replicates of each x value.

Author(s)

Lukasz Komsta

References

see lmcal

See Also

lmcal, nlscal

Examples

x = rep(1:10,10)
y = jitter(x)
fit = lmcal(x,y)
lof(fit)

Example output

Loading required package: MASS
Loading required package: outliers
------------------------------------------
If you use this package, please cite the recent paper containing description of this software:
Komsta, L. Chemometric and statistical evaluation of calibration curves in pharmaceutical analysis 
           - a short review on trends and recommendations. J. AOAC Int. 2012, 95, 3, 669-672.
------------------------------------------
There were 13 warnings (use warnings() to see them)
          SSR       SSPE         F    Pr(>F)
p1 1.47113183 1.38038611 0.7395680 0.6563637
p2 1.46094422 1.38038611 0.7503314 0.6301224
p3 1.46032223 1.38038611 0.8686278 0.5212334
p4 1.44917428 1.38038611 0.8969859 0.4867432
P1 0.23178784 1.38038611        NA        NA
P2 0.22636724 1.38038611        NA        NA
P3 0.22414567 1.38038611        NA        NA
P4 0.22261448 1.38038611        NA        NA
l1 0.05059337 0.04617976 1.0752159 0.3876349
l2 0.04825436 0.04617976 0.5776019 0.7724242
bx 1.45940572 1.38038611 0.6440014 0.7387543
by 1.52278229 1.44117319 0.6370521 0.7446389
r1 1.47132377 1.38038611        NA        NA
r2 1.46232312 1.38038611        NA        NA
r3 1.46176547 1.38038611        NA        NA
r4 1.45066811 1.38038611        NA        NA
R1 0.81285760 1.38038611        NA        NA
R2 1.03537047 1.38038611        NA        NA
R3 1.10342907 1.38038611        NA        NA
R4 0.22875976 1.38038611        NA        NA

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