| Fstats {strucchange} | R Documentation |
Computes a series of F statistics for a specified data window.
Fstats(formula, from = 0.15, to = NULL, data)
formula |
a symbolic description for the model to be tested |
from, to |
numeric. If from is smaller than 1 they are
interpreted as percentages of data and by default to is taken to be
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. If from is a vector with
two elements, then from and {to |
are interpreted as time
specifications like in ts, see also the examples.
For every potential change point in from:to a F statistic (Chow
test statistic) is computed. For this an OLS model is fitted for the
observations before and after the potential change point, i.e. 2k
parameters have to be estimated, and the error sum of squares is computed (ESS).
Another OLS model for all obervations with a restricted sum of squares (RSS) is
computed, hence k parameters have to be estimated here. If n is
the number of observations and k the number of regressors in the model,
the formula is:
F = (RSS-ESS)/ESS * (n-2*k)/k
Fstats returns an object of class "Fstats", which contains
mainly a time series of F statistics. The function plot has a
method to plot the F statistics or the
corresponding p values; with sctest a
supF-, aveF- or expF-test on structural change can be performed.
Achim Zeileis zeileis@ci.tuwien.ac.at
Andrews D.W.K. (1993), Tests for parameter instability and structural change with unknown change point, Econometrica, 61, 821-856.
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.
plot.Fstats, sctest.Fstats,
boundary.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) ## this gives the same result fs <- Fstats(nhtemp ~ 1, from = c(1941,1), to = c(1962,1)) ## 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")