sctest.formula: Structural Change Tests in Linear Regression Models
In strucchangeRcpp: Testing, Monitoring, and Dating Structural Changes: C++ Version

Description Usage Arguments Details Value See Also Examples

Performs tests for structural change in linear regression models.

## S3 method for class 'formula'
sctest(formula, type = , h = 0.15,
    alt.boundary = FALSE, functional = c("max", "range",
    "maxL2", "meanL2"), from = 0.15, to = NULL, point = 0.5,
    asymptotic = FALSE, data, ...)

`formula`	a formula describing the model to be tested.
`type`	a character string specifying the structural change test that is to be performed, the default is `"Rec-CUSUM"`. Besides the test types described in `efp` and `sctest.Fstats` the Chow test and the Nyblom-Hansen test can be performed by setting type to `"Chow"` or `"Nyblom-Hansen"`, respectively.
`h`	numeric from interval (0,1) specifying the bandwidth. Determines the size of the data window relative to the sample size (for MOSUM and ME tests only).
`alt.boundary`	logical. If set to `TRUE` alternative boundaries (instead of the standard linear boundaries) will be used (for CUSUM processes only).
`functional`	indicates which functional should be used to aggregate the empirical fluctuation processes to a test statistic.
`from, to`	numeric. If `from` is smaller than 1 they are interpreted as percentages of data and by default `to` is taken to be the 1 - `from`. F statistics will be calculated for the observations `(nfrom):(nto)`, when `n` is the number of observations in the model. If `from` is greater than 1 it is interpreted to be the index and `to` defaults to `n - from`. (for F tests only)
`point`	parameter of the Chow test for the potential change point. Interpreted analogous to the `from` parameter. By default taken to be `floor(n*0.5)` if `n` is the number of observations in the model.
`asymptotic`	logical. If `TRUE` the asymptotic (chi-square) distribution instead of the exact (F) distribution will be used to compute the p value (for Chow test only).
`data`	an optional data frame containing the variables in the model. By default the variables are taken from the environment which `sctest` is called from.
`...`	further arguments passed to `efp` or `Fstats`.

sctest.formula is a convenience interface for performing structural change tests in linear regression models based on efp and Fstats. It is mainly a wrapper for sctest.efp and sctest.Fstats as it fits an empirical fluctuation process first or computes the F statistics respectively and subsequently performs the corresponding test. The Chow test and the Nyblom-Hansen test are available explicitly here.

An alternative convenience interface for performing structural change tests in general parametric models (based on gefp) is available in sctest.default.

An object of class "htest" containing:

`statistic`	the test statistic,
`p.value`	the corresponding p value,
`method`	a character string with the method used,
`data.name`	a character string with the data name.

sctest.efp, sctest.Fstats, sctest.default

## Example 7.4 from Greene (1993), "Econometric Analysis"
## Chow test on Longley data
data("longley")
sctest(Employed ~ Year + GNP.deflator + GNP + Armed.Forces, data = longley,
  type = "Chow", point = 7)

## which is equivalent to segmenting the regression via
fac <- factor(c(rep(1, 7), rep(2, 9)))
fm0 <- lm(Employed ~ Year + GNP.deflator + GNP + Armed.Forces, data = longley)
fm1 <- lm(Employed ~ fac/(Year + GNP.deflator + GNP + Armed.Forces), data = longley)
anova(fm0, fm1)

## estimates from Table 7.5 in Greene (1993)
summary(fm0)
summary(fm1)