confint.fxregimes {fxregime} | R Documentation

## Confidence Intervals for Breaks Between Exchange Rate Regimes

### Description

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

### Usage

    ## S3 method for class '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., 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. (2008), Testing, Monitoring, and Dating Structural Changes in Maximum Likelihood Models, Report 70, Department of Statistics and Mathematics, Wirtschaftsuniversitaet Wien, Research Report Series, August 2008.

### See Also

`fxregimes`, `refit`, `fxlm`, `confint.breakpointsfull`

### Examples

    ## 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)

[Package fxregime version 0.3-1 Index]