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.

Version: 1.1.0
Depends: R (≥ 3.2.0), lubridate, mgcv
Imports: XML, dataRetrieval, digest, gdata, memoise, methods, plyr, survival, zCompositions
Suggests: devtools, fitdistrplus, imputeTS, knitr, nlme, pander, readxl, rmarkdown, sessioninfo, testthat
Published: 2019-03-14
Author: Rebecca Murphy, Elgin Perry, Jennifer Keisman, Jon Harcum, Erik W Leppo
Maintainer: Erik Leppo <Erik.Leppo at tetratech.com>
License: GPL-3
URL: https://github.com/tetratech/baytrends
NeedsCompilation: no
Materials: README NEWS
CRAN checks: baytrends results

Downloads:

Reference manual: baytrends.pdf
Vignettes: Data Sets
QW
Package source: baytrends_1.1.0.tar.gz
Windows binaries: r-devel: baytrends_1.1.0.zip, r-devel-gcc8: baytrends_1.1.0.zip, r-release: baytrends_1.1.0.zip, r-oldrel: baytrends_1.1.0.zip
OS X binaries: r-release: baytrends_1.1.0.tgz, r-oldrel: baytrends_1.1.0.tgz
Old sources: baytrends archive

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