unSurvDF

Converts Surv objects in a dataframe to "lo" (i.e., lower) and
 "hi" (i.e., upper) values. The user can specify their own values or use the
 defaults.

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

unSurvDF function

<dl><dt>df</dt>
<dd>dataframe with Surv objects</dd>
<dt>suf_lo</dt>
<dd>Column name suffix for "lo" values. Default = "_lo"</dd>
<dt>suf_hi</dt>
<dd>Column name suffix for "hi" values. Default = "_hi"</dd></dl>

Arguments

Converts Surv objects in a dataframe to "lo" and "hi" values — unSurvDF

<dl>

<dt>df</dt>
<dd>dataframe with Surv objects</dd>


<dt>suf_lo</dt>
<dd>Column name suffix for "lo" values. Default = "_lo"</dd>


<dt>suf_hi</dt>
<dd>Column name suffix for "hi" values. Default = "_hi"</dd>

</dl>

unSurvDF: Converts Surv objects in a dataframe to "lo" and "hi" values

Description

Usage

Value

Arguments

See Also

Examples