Given a segmented model (typically returned by a segmented
method), broken.line
computes the fitted values (and relevant standard errors) for the specified `segmented' relationship.
broken.line(ogg, term = NULL, link = TRUE, interc=TRUE, se.fit=TRUE, isV=FALSE,
.vcov=NULL, .coef=NULL, ...)
A list having one component if (if se.fit=FALSE
), and two components (if se.fit=TRUE
) list representing predictions and standard errors for the segmented covariate values.
A fitted object of class segmented (returned by any segmented
method).
Three options. i) A named list (whose name should be one of the segmented covariates in the model ogg
)
including the covariate values for which segmented predictions should be computed; ii) a character meaning
the name of any segmented covariate in the model (and predictions corresponding to the observed covariate values are returned);
iii) It can be NULL
if the model includes a single segmented covariate (and predictions corresponding to the observed covariate values are returned).
Should the predictions be computed on the scale of the link function if ogg
is a segmented glm fit? Default to TRUE
.
Should the model intercept be added? (provided it exists).
If TRUE
also standard errors for predictions are returned.
A couple of logicals indicating if the segmented terms \((x-\psi)_+\) and \(I(x>\psi)\) in the model matrix should be replaced by their smoothed counterparts when computing the standard errors. If a single logical is provided, it is applied to both terms.
Optional. The full covariance matrix of estimates. If NULL
(and se.fit=TRUE
), the matrix is computed internally via vcov.segmented()
.
The regression parameter estimates. If unspecified (i.e. NULL
), it is computed internally by coef(ogg)
.
Additional arguments to be passed on to vcov.segmented()
when computing the standard errors for the predictions, namely
is
, var.diff
, p.df
. See summary.segmented
and vcov.segmented
.
Vito M. R. Muggeo
If term=NULL
or term
is a valid segmented covariate name,
predictions for that 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 possible 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".
segmented
, predict.segmented
, plot.segmented
, vcov.segmented
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)
if (FALSE) plot(z,y)
if (FALSE) points(z,broken.line(o.seg,link=FALSE)$fit,col=2) #ok, but use plot.segmented()!
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