segmented: Regression Models with Break-Points / Change-Points (with
Possibly Random Effects) Estimation
Given a regression model, segmented ‘updates’ it by adding one or more segmented
(i.e., piece-wise linear) relationships. Several variables with multiple breakpoints are allowed. The estimation method is discussed in Muggeo (2003, <doi:10.1002/sim.1545>) and
illustrated in Muggeo (2008, <https://www.r-project.org/doc/Rnews/Rnews_2008-1.pdf>). An approach for hypothesis testing is presented
in Muggeo (2016, <doi:10.1080/00949655.2016.1149855>), and interval estimation for the breakpoint is discussed in Muggeo (2017, <doi:10.1111/anzs.12200>).
Segmented mixed models, i.e. random effects in the change point, are discussed in
in Muggeo (2014, <doi:10.1177/1471082X13504721>).
Documentation:
Downloads:
Reverse dependencies:
| Reverse imports: |
AQEval, ddiv, lactater, mixtools, netSEM, PCRedux, PUPAK, PVplr, rcssci, respirometry, respR, seqinr, spatialwarnings, SWTools, takos, Trendy, weibulltools |
| Reverse suggests: |
nlraa, REddyProc |
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