baytrends: Long Term Water Quality Trend Analysis

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: 2.0.5
Depends: R (≥ 3.5.0)
Imports: dataRetrieval, digest, lubridate, memoise, mgcv, plyr, survival
Suggests: devtools, dplyr, fitdistrplus, grDevices, imputeTS, knitr, markdown, nlme, pander, readxl, rmarkdown, sessioninfo, testthat
Published: 2021-05-14
Author: Rebecca Murphy, Elgin Perry, Jennifer Keisman, Jon Harcum, Erik W Leppo
Maintainer: Erik W Leppo <Erik.Leppo at>
License: GPL-3
NeedsCompilation: no
Materials: README NEWS
CRAN checks: baytrends results


Reference manual: baytrends.pdf
Vignettes: Flow and Salinity Data Sets
Processing Censored Water Quality Data


Package source: baytrends_2.0.5.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): baytrends_2.0.5.tgz, r-release (x86_64): baytrends_2.0.5.tgz, r-oldrel: baytrends_2.0.5.tgz
Old sources: baytrends archive


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