.gamDiffPORtbl

Compute and present report on percent different for log-transformed data

internal

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>.

Erik Leppo

baytrends

Long Term Water Quality Trend Analysis

.gamDiffPORtbl function

<dl><dt>por.diff</dt>
<dd>Output from gam.por.diff</dd>
<dt>iSpec</dt>
<dd>data set specifications</dd></dl>

Arguments

Compute and present report on percent different for log-transformed data — .gamDiffPORtbl

<dl>

<dt>por.diff</dt>
<dd>Output from gam.por.diff</dd>


<dt>iSpec</dt>
<dd>data set specifications</dd>

</dl>

.gamDiffPORtbl: Compute and present report on percent different for log-transformed data

Description

Usage

Arguments