R: Fitted values for segmented relationships

broken.line {segmented} | R Documentation

## Fitted values for segmented relationships

### Description

Given a segmented model (typically returned by a `segmented` method), `broken.line` computes the fitted values (and relevant standard errors) for each ‘segmented’ relationship.

### Usage

    broken.line(ogg, term = NULL, link = TRUE, interc=TRUE, se.fit=TRUE)

### Arguments

`ogg` | A fitted object of class segmented (returned by any `segmented` method).
`term` | Three options. A list (whose name should be one of the segmented covariates) including values for which segmented predictions should be computed. A character meaning the name of any segmented covariate in the model. `NULL` if the model includes a single segmented covariate.
`link` | Should the predictions be computed on the scale of the link function? Default to `TRUE`.
`interc` | Should the model intercept be added? (provided it exists).
`se.fit` | If `TRUE` also standard errors for predictions are returned.

### Details

If `term=NULL` or `term` is a valid segmented covariate name, predictions for each segmented variable are the relevant fitted values from the model. If `term` is a (correctly named) list with numerical values, predictions corresponding to such specified values are computed. If `link=FALSE` and `ogg` inherits from the class "glm", predictions and standard errors are returned on the response scale. The standard errors come from the Delta method. Argument `link` is ignored whether `ogg` does not inherit from the class "glm".

### Value

A 2-component (if `se.fit=TRUE`) list representing predictions and standard errors for the segmented covariate values.

### Author(s)

Vito M. R. Muggeo

### See Also

`segmented`, `predict.segmented`, `plot.segmented`

### Examples

    set.seed(1234)
    z<-runif(100)
    y<-rpois(100,exp(2+1.8*pmax(z-.6,0)))
    o<-glm(y~z,family=poisson)
    o.seg<-segmented(o,seg.Z=~z,psi=.5)
    ## Not run: plot(z,y)
    ## Not run: points(z,broken.line(o.seg,link=FALSE)$fit,col=2) #just to illustrate, use plot.segmented

[Package segmented version 0.5-3.0 Index]