# confint.fxregimes

##### Confidence Intervals for Breaks Between Exchange Rate Regimes

Confidence intervals for estimated changes/breaks between exchange rate regimes.

- Keywords
- regression

##### Usage

```
# S3 method for fxregimes
confint(object, parm = NULL, level = 0.95, breaks = NULL, meat. = NULL, …)
```

##### Arguments

- object
An object of class

`"fxregimes"`

as fitted by`fxregimes`

.- parm
integer. Either

`parm`

or`breaks`

may be set, see below.- level
numeric. The confidence level to be used.

- breaks
integer. The number of breaks to be extracted from

`object`

for which confidence intervals should be computed.- meat.
function. A function for extracting the meat of a sandwich estimator from a

`fxlm`

object. By default, the inverse of`bread`

is used, i.e., a correctly specified model is assumed.- …
currently not used.

##### Details

As the breakpoints are integers (observation numbers) the corresponding
confidence intervals are also rounded to integers. The algorithm used
is essentially the same as described for `confint.breakpointsfull`

.
The same distribution function is used, just the variance components are
computed differently. Here, `bread`

and
`meat`

(or some of its HC/HAC counterparts) are
used. See Zeileis, Shah, Patnaik (2008) for more details.

##### Value

An object of class `"confint.fxregimes"`

.

##### References

Zeileis A., Kleiber C., Kr<e4>mer W., Hornik K. (2003), Testing and Dating of
Structural Changes in Practice, *Computational Statistics and Data Analysis*,
**44**, 109--123.

Zeileis A., Shah A., Patnaik I. (2010), Testing, Monitoring, and Dating Structural
Changes in Exchange Rate Regimes, *Computational Statistics and Data Analysis*,
54(6), 1696--1706. http://dx.doi.org/10.1016/j.csda.2009.12.005.

##### See Also

##### Examples

```
# NOT RUN {
## load package and data
library("fxregime")
data("FXRatesCHF", package = "fxregime")
## compute returns for CNY (and explanatory currencies)
## for one year after abolishing fixed USD regime
cny <- fxreturns("CNY", frequency = "daily",
start = as.Date("2005-07-25"), end = as.Date("2006-07-24"),
other = c("USD", "JPY", "EUR", "GBP"))
## compute all segmented regression with minimal segment size of
## h = 20 and maximal number of breaks = 5.
reg <- fxregimes(CNY ~ USD + JPY + EUR + GBP,
data = cny, h = 20, breaks = 5, ic = "BIC")
summary(reg)
## minimum BIC is attained for 2-segment (1-break) model
plot(reg)
## two regimes
## 1: tight USD peg
## 2: slightly more relaxed USD peg
round(coef(reg), digits = 3)
sqrt(coef(reg)[, "(Variance)"])
## inspect associated confidence intervals
ci <- confint(reg, level = 0.9)
ci
breakdates(ci)
## plot LM statistics along with confidence interval
fm <- fxlm(CNY ~ USD + JPY + EUR + GBP, data = cny)
scus <- gefp(fm, fit = NULL)
plot(scus, functional = supLM(0.1))
lines(ci)
# }
```

*Documentation reproduced from package fxregime, version 1.0-4, License: GPL-2 | GPL-3*