R AQEval: R code for the analysis of discrete change in Air Quality time-series.
AQEval
AQEval was developed for use by those tasked with
the routine detection, characterisation and quantification
of discrete changes in air quality time-series.
The main functions, quantBreakPoints
and quantBreakSegments, use
break-point/segment (BP/S) methods
based on the consecutive use of methods in the
strucchange and segmented R packages
to first detection (as break-points) and then characterise
and quantify (as segments), discrete changes in
air-quality time-series.
AQEval functions adopt an openair-friendly
approach using function and data structures that many
in the air quality research community are already familiar
with.
Most notably, most functions expect supplied data
to be time-series, to be supplied as a single
data.frame (or similar R object), and for
time-series to be identified by column names.
The main functions are typically structured expect
first the data.frame, then the name of the
pollutant to be used, then other arguments:
function(data, "polluant.name", ...)
output <- function(data, "polluant.name", ...)
See also
For more about data structure and an example data set,
see AQEval.data
For more about the main functions, see
quantBreakPoints
and quantBreakSegments