Description Usage Arguments Details Value References See Also Examples
Computes confidence intervals for breakpoints.
1 2 3 4 5 6  ## S3 method for class 'breakpointsfull'
confint(object, parm = NULL, level = 0.95,
breaks = NULL, het.reg = TRUE, het.err = TRUE, vcov. = NULL, sandwich = TRUE, ...)
## S3 method for class 'confint.breakpoints'
lines(x, col = 2, angle = 90, length = 0.05,
code = 3, at = NULL, breakpoints = TRUE, ...)

object 
an object of class 
parm 
the same as 
level 
the confidence level required. 
breaks 
an integer specifying the number of breaks to be used. By default the breaks of the minimum BIC partition are used. 
het.reg 
logical. Should heterogeneous regressors be assumed? If set
to 
het.err 
logical. Should heterogeneous errors be assumed? If set
to 
vcov. 
a function to extract the covariance matrix
for the coefficients of a fitted model of class 
sandwich 
logical. Is the function 
x 
an object of class 
col, angle, length, code 
arguments passed to 
at 
position on the y axis, where the confidence arrows should be drawn. By default they are drawn at the bottom of the plot. 
breakpoints 
logical. If 
... 
currently not used. 
As the breakpoints are integers (observation numbers) the corresponding confidence intervals are also rounded to integers.
The distribution function used for the computation of confidence intervals of breakpoints is given in Bai (1997). The procedure, in particular the usage of heterogeneous regressors and/or errors, is described in more detail in Bai & Perron (2003).
The breakpoints should be computed from a formula with breakpoints
,
then the confidence intervals for the breakpoints can be derived by
confint
and these can be visualized by lines
. For an
example see below.
A matrix containing the breakpoints and their lower and upper confidence boundary for the given level.
Bai J. (1997), Estimation of a Change Point in Multiple Regression Models, Review of Economics and Statistics, 79, 551563.
Bai J., Perron P. (2003), Computation and Analysis of Multiple Structural Change Models, Journal of Applied Econometrics, 18, 122.
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