Use 'investr' conditionally in tests, updates

Most prominently, a README was added, giving a nice
overview for the people visiting the github page, the
package page on CRAN, or the online docs at pkgdown.jrwb.de.
The maintainer e-mail address was also updated.

1 files changed, 103 insertions, 0 deletions

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://www.r-pkg.org/badges/version/chemCal)](https://cran.r-project.org/package=chemCal)
+[![Build Status](https://travis-ci.com/jranke/chemCal.svg?branch=master)](https://app.travis-ci.com/github/jranke/chemCal)
+[![codecov](https://codecov.io/github/jranke/chemCal/branch/master/graphs/badge.svg)](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