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coverage](https://codecov.io/gh/zsteinmetz/envalysis/branch/main/graph/badge.svg)](https://app.codecov.io/gh/zsteinmetz/envalysis?branch=main)\n[![License](https://img.shields.io/badge/license-GPL--3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0)\n[![Downloads](https://cranlogs.r-pkg.org/badges/grand-total/envalysis)](https://CRAN.R-project.org/package=envalysis)\n[![DOI](https://img.shields.io/badge/shortDOI-10/ft9p-blue.svg)](https://doi.org/10.5281/ZENODO.1240304)\n\u003c!-- badges: end --\u003e\n\n**envalysis** is an R package containing miscellaneous functions for data\nanalysis in environmental chemistry and ecotoxicology. Provides, for example,\n`calibration()` to calculate calibration curves and corresponding limits of\ndetection (LODs) and limits of quantification (LOQs) according to German DIN\n32645 (2008). `texture()` makes it easy to estimate soil particle size\ndistributions from hydrometer measurements (ASTM D422-63, 2007). Some functions\nof the package require **ggplot2** or **drc**.\n\n## Functions\n\nThe following functions are available:\n\n### Data manipulation and analysis\n\n* Calculating limits of detection `lod()` and limits of quantification `loq()`\n  as part of the `'calibration'` class to produce linear calibration curves\n  in accordance with German DIN 32645 (2008); see\n  [vignette](https://zsteinmetz.de/envalysis/articles/calibration.html) for\n  details\n* Calculating concentrations from calibration curves using `inv_predict()`\n* Finding optimum weights for weighted calibrations using `weight_select()`\n* Estimating matrix effects (signal suppression/enhancement) with\n  `matrix_effect()`\n* Determining particle size distributions and soil texture classes (DIN/USDA)\n  measured with a soil hydrometer in accordance with ASTM D422-63 (2007) using\n  `texture()`; see\n  [vignette](https://zsteinmetz.de/envalysis/articles/texture.html) for details\n* Confidence intervals `CI()`, standard errors `se()`, and root mean square\n  errors `rmse()`\n* Various sorption isotherms `sorption()`\n\n### Data presentation\n\n* Categorize water drop penetration times according to Bisdom et al. (1993)\n  with `bisdom()`\n* Report significant figures, namely round means and errors to the least\n  significant digit, using `signifig()`\n* Clean, black-and-white ggplot2 theme for scientific publications\n  `theme_publish()`; a preview is available\n  [here](https://zsteinmetz.de/envalysis/articles/theme_publish.html)\n\n## Installation\n\n**envalysis** is available on CRAN and GitHub.\n\n### Install from CRAN (stable version)\n\nYou can install the released version of **envalysis** from\n[CRAN](https://cran.r-project.org/package=envalysis) with:\n\n```r\ninstall.packages(\"envalysis\")\n```\n\n### Install from GitHub (development version)\n\nTo install the development version of this package, paste the following code\ninto your R console (requires **devtools**):\n\n```r\nif(!require(devtools)) install.packages(\"devtools\")\ndevtools::install_github(\"zsteinmetz/envalysis\")\n```\n","funding_links":["https://github.com/sponsors/zsteinmetz"],"readme_doi_urls":["https://doi.org/10.5281/ZENODO.1240304"],"works":{"https://doi.org/10.5281/ZENODO.1240304":null},"citation_counts":{},"total_citations":0,"keywords_from_contributors":[],"project_url":"https://ost.ecosyste.ms/api/v1/projects/18000","html_url":"https://ost.ecosyste.ms/projects/18000"}