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diff --git a/README.rmd b/README.rmd new file mode 100644 index 0000000..6b027f4 --- /dev/null +++ b/README.rmd @@ -0,0 +1,103 @@ +--- +output: github_document +--- + +<!-- README.md is generated from README.rmd. Please edit that file --> + +```{r, echo = FALSE} +knitr::opts_chunk$set( + collapse = TRUE, + comment = "#>", + fig.path = "man/figures/README-" +) +``` + +# chemCal - Calibration functions for analytical chemistry + +<!-- badges: start --> +[](https://cran.r-project.org/package=chemCal) +[](https://app.travis-ci.com/github/jranke/chemCal) +[](https://codecov.io/github/jranke/chemCal) +<!-- badges: end --> + +## Overview + +chemCal is an R package providing some basic functions for conveniently working +with linear calibration curves with one explanatory variable. + +## Installation + +From within [R][r-project], get the official chemCal release using + +```{r, eval = FALSE} +install.packages("chemCal") +``` + +## Usage + +chemCal works with univariate linear models of class `lm`. Working with one of +the datasets coming with chemCal, we can produce a calibration plot using the +`calplot` function: + +### Plotting a calibration + +```{r calplot} +library(chemCal) +m0 <- lm(y ~ x, data = massart97ex3) +calplot(m0) +``` + +### LOD and LOQ + +If you use unweighted regression, as in the above example, we can calculate a +Limit Of Detection (LOD) from the calibration data. + +```{r} +lod(m0) +``` +This is the minimum detectable value (German: Erfassungsgrenze), i.e. the +value where the probability that the signal is not detected although the +analyte is present is below a specified error tolerance beta (default is 0.05 +following the IUPAC recommendation). + +You can also calculate the decision limit (German: Nachweisgrenze), i.e. +the value that is significantly different from the blank signal +with an error tolerance alpha (default is 0.05, again following +IUPAC recommendations) by setting beta to 0.5. + +```{r} +lod(m0, beta = 0.5) +``` + +Furthermore, you can calculate the Limit Of Quantification (LOQ), being +defined as the value where the relative error of the quantification given the +calibration model reaches a prespecified value (default is 1/3). + +```{r} +loq(m0) +``` + +### Confidence intervals for measured values + +Finally, you can get a confidence interval for the values +measured using the calibration curve, i.e. for the inverse +predictions using the function `inverse.predict`. + +```{r} +inverse.predict(m0, 90) +``` + +If you have replicate measurements of the same sample, +you can also give a vector of numbers. + +```{r} +inverse.predict(m0, c(91, 89, 87, 93, 90)) +``` + +## Reference + +You can use the R help system to view documentation, or you can +have a look at the [online documentation][pd-site]. + +[r-project]: https://r-project.org +[pd-site]: https://pkgdown.jrwb.de/chemCal |