| sctest.Fstats | R Documentation | 
Performs the supF-, aveF- or expF-test
## S3 method for class 'Fstats'
sctest(x, type = c("supF", "aveF", "expF"),
    asymptotic = FALSE, ...)
x | 
 an object of class   | 
type | 
 a character string specifying which test will be performed.  | 
asymptotic | 
 logical. Only necessary if   | 
... | 
 currently not used.  | 
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 https://www.ssc.wisc.edu/~bhansen/. R port by Achim Zeileis.
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.  | 
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.
Fstats, plot.Fstats
## 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")
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