Finding and testing break-points in conventionally formatted air quality data sets.
Arguments
- data
Data source, typically a
data.frame
or similar, containing data-series to apply function to and a paired time-stamped data-series, calleddate
.- pollutant
Name of time-series, assumed to be a column in
date
.- h
(
findBreakPoints
only) The data/time window size to use when looking for breaks in a supplied time-series, expressed as proportion of time-series (0-1), default 0.15.- ...
other parameters
- breaks
(
testBreakPoints
only)data.frame
of The break-points and confidence intervals, typically afindBreakPoints
output.
Value
findBreakPoints
returns a data.frame
of found break-points.
testBreakPoints
return a likely break-point/segment
report.
Details
findBreakPoints
uses methods from
strucchange
package (see references) and
modifications as suggested by the main author of
strucchange
to handle missing cases to find
potential breaks-points in a supplied time-series.
testBreakPoints
tests and identifies most likely
break-points using methods proposed for use with
quantBreakPoints
and quantBreakSegments
and conventionally formatted air quality data sets.
References
Regarding strucchange
methods see
breakpoints
, and:
Achim Zeileis, Friedrich Leisch, Kurt Hornik and Christian Kleiber (2002). strucchange: An R Package for Testing for Structural Change in Linear Regression Models. Journal of Statistical Software, 7(2), 1-38. URL https://www.jstatsoft.org/v07/i02/.
Achim Zeileis, Christian Kleiber, Walter Kraemer and Kurt Hornik (2003). Testing and Dating of Structural Changes in Practice. Computational Statistics & Data Analysis, 44, 109-123.
Regarding missing data handling, see:
URL: https://stackoverflow.com/questions/43243548/strucchange-not-reporting-breakdates.
Regarding testBreakPoints
, see:
Ropkins et al (In Prep).