doi:10.1016/j.envsoft.2019.03.027>.">

baytrends: Long Term Water Quality Trend Analysis (original) (raw)

Enable users to evaluate long-term trends using a Generalized Additive Modeling (GAM) approach. The model development includes selecting a GAM structure to describe nonlinear seasonally-varying changes over time, incorporation of hydrologic variability via either a river flow or salinity, the use of an intervention to deal with method or laboratory changes suspected to impact data values, and representation of left- and interval-censored data. The approach has been applied to water quality data in the Chesapeake Bay, a major estuary on the east coast of the United States to provide insights to a range of management- and research-focused questions. Methodology described in Murphy (2019) <doi:10.1016/j.envsoft.2019.03.027>.

Version: 2.0.12
Depends: R (≥ 3.5.0)
Imports: dataRetrieval, digest, dplyr, fitdistrplus, grDevices, lubridate, knitr, memoise, mgcv, pander, plyr, readxl, sessioninfo, survival
Suggests: devtools, imputeTS, markdown, nlme, rmarkdown, testthat
Published: 2024-07-26
DOI: 10.32614/CRAN.package.baytrends
Author: Rebecca Murphy, Elgin Perry, Jennifer Keisman, Jon Harcum, Erik W Leppo
Maintainer: Erik W Leppo <Erik.Leppo at tetratech.com>
BugReports: https://github.com/tetratech/baytrends/issues
License: GPL-3
URL: https://github.com/tetratech/baytrends,https://tetratech.github.io/baytrends/
NeedsCompilation: no
Materials: README NEWS
In views: Hydrology
CRAN checks: baytrends results

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