Confidence Intervals for Breakpoints
Computes confidence intervals for breakpoints.
## 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, 551-563.
Bai J., Perron P. (2003), Computation and Analysis of Multiple Structural Change Models, Journal of Applied Econometrics, 18, 1-22.
## Nile data with one breakpoint: the annual flows drop in 1898
## because the first Ashwan dam was built
data("Nile")
plot(Nile)
## dating breaks
bp.nile <- breakpoints(Nile ~ 1)
ci.nile <- confint(bp.nile, breaks = 1)
lines(ci.nile)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.