R: Segmented relationships in regression models with breakpoints...

segmented-package {segmented} | R Documentation

## Segmented relationships in regression models with breakpoints / changepoints estimation

### Description

Estimation and Inference of Regression Models with piecewise linear relationships having a fixed number of break-points.

### Details

Package: | segmented
Type: | Package
Version: | 0.5-3.0
Date: | 2017-11-22
License: | GPL

Package `segmented` is aimed to estimate linear and generalized linear models (and virtually any regression model) having one or more segmented relationships in the linear predictor. Estimates of the slopes and breakpoints are provided along with standard errors. The package includes testing/estimating functions and methods to print, summarize and plot the results.

The algorithm used by `segmented` is not grid-search. It is an iterative procedure (Muggeo, 2003) that needs starting values only for the breakpoint parameters and therefore it is quite efficient even with several breakpoints to be estimated. Moreover since version 0.2-9.0, `segmented` implements the bootstrap restarting (Wood, 2001) to make the algorithm less sensitive to starting values.

Since version 0.5-0.0 a default method `segmented.dafault` has been added. It may be employed to include segmented relationships in general regression models where specific methods do not exist. Examples include quantile and Cox regressions. See examples in `segmented.default`.

A tentative approach to deal with unknown number of breakpoints is also provided, see option `stop.if.error` in `seg.control`.

### Author(s)

Vito M.R. Muggeo <vito.muggeo@unipa.it>

### References

Muggeo, V.M.R. (2016) Testing with a nuisance parameter present only under the alternative: a score-based approach with application to segmented modelling. J of Statistical Computation and Simulation 86, 3059–3067.

Davies, R.B. (1987) Hypothesis testing when a nuisance parameter is present only under the alternative. Biometrika 74, 33–43.

Seber, G.A.F. and Wild, C.J. (1989) Nonlinear Regression. Wiley, New York.

Bacon D.W., Watts D.G. (1971) Estimating the transistion between two intersecting straight lines. Biometrika 58: 525 – 534.

Muggeo, V.M.R. (2003) Estimating regression models with unknown break-points. Statistics in Medicine 22, 3055–3071.

Muggeo, V.M.R. (2008) Segmented: an R package to fit regression models with broken-line relationships. R News 8/1, 20–25.

Muggeo, V.M.R., Adelfio, G. (2011) Efficient change point detection in genomic sequences of continuous measurements. Bioinformatics 27, 161–166.

Wood, S. N. (2001) Minimizing model fitting objectives that contain spurious local minima by bootstrap restarting. Biometrics 57, 240–244.

Muggeo, V.M.R. (2010) Comment on ‘Estimating average annual per cent change in trend analysis’ by Clegg et al., Statistics in Medicine; 28, 3670-3682. Statistics in Medicine, 29, 1958–1960.

[Package segmented version 0.5-3.0 Index]