baytrends-package: baytrends: Long Term Water Quality Trend Analysis
In leppott/baytrends033: Long Term Water Quality Trend Analysis
baytrends-package R Documentation
baytrends: Long Term Water Quality Trend Analysis
Description
The baytrends package was developed to enable users to evaluate long-term
trends in the Chesapeake Bay 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. This
approach, which is fully transferable to other systems, allows for Chesapeake
Bay water quality data to be evaluated in a statistically rigorous, yet
flexible way to provide insights to a range of management- and
research-focused questions. Methodology described in Murphy, RR, E Perry,
J Harcum, and J Keisman 2019 A Generalized Additive Model approach to
evaluating water quality: Chesapeake Bay case study. Environmental Modelling
& Software, 118 (2019) 1-13.
<https://doi.org/10.1016/j.envsoft.2019.03.027>.
Details
This software program is preliminary or provisional and is subject
to revision. This software program is for testing only, no warranty,
expressed or implied, is made as to the accuracy and functioning of the
program and related program material nor shall the fact of distribution
constitute any such warranty, and no responsibility is assumed in connection
therewith. This software is provided 'AS IS.
See Also
Useful links:
leppott/baytrends033 documentation built on Feb. 17, 2024, 9:27 a.m.
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| baytrends-package | R Documentation |
baytrends: Long Term Water Quality Trend Analysis
Description
The baytrends package was developed to enable users to evaluate long-term trends in the Chesapeake Bay 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. This approach, which is fully transferable to other systems, allows for Chesapeake Bay water quality data to be evaluated in a statistically rigorous, yet flexible way to provide insights to a range of management- and research-focused questions. Methodology described in Murphy, RR, E Perry, J Harcum, and J Keisman 2019 A Generalized Additive Model approach to evaluating water quality: Chesapeake Bay case study. Environmental Modelling & Software, 118 (2019) 1-13. <https://doi.org/10.1016/j.envsoft.2019.03.027>.
Details
This software program is preliminary or provisional and is subject to revision. This software program is for testing only, no warranty, expressed or implied, is made as to the accuracy and functioning of the program and related program material nor shall the fact of distribution constitute any such warranty, and no responsibility is assumed in connection therewith. This software is provided 'AS IS.
See Also
Useful links:
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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