QC_invalidateConsecutiveSuspectValues

Invalidates values within a timeseries that appear "sticky".
Some temporary monitoring data has stretches of consecutive values, sometimes
well outside the range of reasonable. This QC function identifies these
"sticky" stretches and returns the original timeseries data with "sticky"
stretches replaced with <code>NA</code>.

Utilities for working with hourly air quality monitoring data
with a focus on small particulates (PM2.5). A compact data model is
structured as a list with two dataframes. A 'meta' dataframe contains
spatial and measuring device metadata associated with deployments at known
locations. A 'data' dataframe contains a 'datetime' column followed by
columns of measurements associated with each "device-deployment".
Algorithms to calculate NowCast and the associated Air Quality Index (AQI)
are defined at the US Environmental Projection Agency AirNow program:
<https://document.airnow.gov/technical-assistance-document-for-the-reporting-of-daily-air-quailty.pdf>.

Jonathan Callahan

AirMonitor

Air Quality Data Analysis

Spencer Pease

Hans Martin

Rex Thompson

QC_invalidateConsecutiveSuspectValues function

<dl><dt>x</dt>
<dd>Timeseries data.</dd>
<dt>suspectValues</dt>
<dd>Vector of numeric values considered suspect.</dd>
<dt>consecutiveCount</dt>
<dd>How many <code>suspectValues</code> must appear in a row
before they are invalidated.</dd></dl>

Arguments

Invalidate consecutive suspect values. — QC_invalidateConsecutiveSuspectValues

<dl>

<dt>x</dt>
<dd>Timeseries data.</dd>


<dt>suspectValues</dt>
<dd>Vector of numeric values considered suspect.</dd>


<dt>consecutiveCount</dt>
<dd>How many <code>suspectValues</code> must appear in a row
before they are invalidated.</dd>

</dl>

QC_invalidateConsecutiveSuspectValues: Invalidate consecutive suspect values.

Description

Usage

Value

Arguments