R: supF-, aveF- and expF-Test

sctest.Fstats {strucchange} | R Documentation

## supF-, aveF- and expF-Test

### Description

Performs the supF-, aveF- or expF-test

### Usage

    ## S3 method for class 'Fstats'
    sctest(x, type = c("supF", "aveF", "expF"),
        asymptotic = FALSE, ...)

### Arguments

`x` | an object of class `"Fstats"`.
`type` | a character string specifying which test will be performed.
`asymptotic` | logical. Only necessary if `x` contains just a single F statistic and type is `"supF"` or `"aveF"`. If then set to `TRUE` the asymptotic (chi-square) distribution instead of the exact (F) distribution will be used to compute the p value.
`...` | currently not used.

### Details

If `x` contains just a single F statistic and type is `"supF"` or `"aveF"` the Chow test will be performed.

The original GAUSS code for computing the p values of the supF-, aveF- and expF-test was written by Bruce Hansen and is available from http://www.ssc.wisc.edu/~bhansen/. R port by Achim Zeileis.

### 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.

### References

Andrews D.W.K. (1993), Tests for parameter instability and structural change with unknown change point, Econometrica, 61, 821-856.

Andrews D.W.K., Ploberger W. (1994), Optimal tests when a nuisance parameter is present only under the alternative, Econometrica, 62, 1383-1414.

Hansen B. (1992), Tests for parameter instability in regressions with I(1) processes, Journal of Business & Economic Statistics, 10, 321-335.

Hansen B. (1997), Approximate asymptotic p values for structural-change tests, Journal of Business & Economic Statistics, 15, 60-67.

### See Also

`Fstats`, `plot.Fstats`

### Examples

    ## Load dataset "nhtemp" with average yearly temperatures in New Haven
    data(nhtemp)
    ## plot the data
    plot(nhtemp)

    ## test the model null hypothesis that the average temperature remains
    ## constant over the years for potential break points between 1941
    ## (corresponds to from = 0.5) and 1962 (corresponds to to = 0.85)
    ## compute F statistics
    fs <- Fstats(nhtemp ~ 1, from = 0.5, to = 0.85)
    ## plot the F statistics
    plot(fs, alpha = 0.01)
    ## and the corresponding p values
    plot(fs, pval = TRUE, alpha = 0.01)
    ## perform the aveF test
    sctest(fs, type = "aveF")

[Package strucchange version 1.5-2 Index]