# sctest.Fstats

##### supF-, aveF- and expF-Test

Performs the supF-, aveF- or expF-test

- Keywords
- htest

##### Usage

```
# S3 method for 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:

the test statistic,

the corresponding p value,

a character string with the method used,

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

##### Examples

```
# NOT RUN {
## 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")
# }
```

*Documentation reproduced from package strucchange, version 1.5-2, License: GPL-2 | GPL-3*