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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", ...)

References

Ropkins et al (In Prep).

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

Author

Karl Ropkins