quantchem v0.13

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Quantitative chemical analysis: calibration and evaluation of results

Statistical evaluation of calibration curves by different regression techniques: ordinary, weighted, robust (up to 4th order polynomial). Log-log and Box-Cox transform, estimation of optimal power and weighting scheme. Tests for heteroscedascity and normality of residuals. Different kinds of plots commonly used in illustrating calibrations. Easy "inverse prediction" of concentration by given responses and statistical evaluation of results (comparison of precision and accuracy by common tests).

Functions in quantchem

Name Description
summary.lmcal, summary.nlscal Summarizing fitted calibration curves
lmcal, nlscal Perform linear and nonlinear calibration of analytical method
lof Lack-of-Fit testing of calibration models
plot.lmcal, plot.nlscal Calibration plots
ibuprofen, genisten, biochanin, pseudoephedrine, nitrate Calibration data for several compounds
residuals.cal Residuals of calibration curves
AIC.cal Akaike's An Information Criterion for calibration models
confint.cal Confidence intervals for calibration curve parameters
predict.lmcal, predict.nlscal Inverse predict concentration from given responses
anova.lmcal, anova.nlscal ANOVA tests for calibration models
vstat Variability statistics of quantitative analysis results
dstat Descriptive statistics of quantitative analysis results
derivative Derivative of fitted polynomial
tablets Tablet mass data
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Type Package
Date 2012-08-20
License GPL (>= 2)
URL http://www.r-project.org, http://www.komsta.net/
Packaged 2012-08-20 14:05:32 UTC; Administrator
Repository CRAN
Date/Publication 2012-08-20 14:19:08

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