R: Structural Change Tests in Linear Regression Models

sctest.formula {strucchange} | R Documentation

## Structural Change Tests in Linear Regression Models

### Description

Performs tests for structural change in linear regression models.

### Usage

    ## 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, ...)

### Arguments

`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 `(n*from):(n*to)`, 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`.

### Details

`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`.

### Value

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.

### See Also

`sctest.efp`, `sctest.Fstats`, `sctest.default`

### Examples

    ## 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)

[Package strucchange version 1.5-2 Index]