Description Usage Arguments Details Value References See Also Examples

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

1 2 |

`object` |
An object of class |

`parm` |
integer. Either |

`level` |
numeric. The confidence level to be used. |

`breaks` |
integer. The number of breaks to be extracted from |

`meat.` |
function. A function for extracting the meat of a sandwich estimator
from a |

`...` |
currently not used. |

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.

An object of class `"confint.fxregimes"`

.

Zeileis A., Kleiber C., Krämer 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.

`fxregimes`

, `refit`

,
`fxlm`

, `confint.breakpointsfull`

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 | ```
## 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)
``` |

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