gefp(..., fit = glm, scores = estfun, vcov = NULL,
decorrelate = TRUE, sandwich = TRUE, order.by = NULL,
fitArgs = NULL, parm = NULL, data = list())
data
to the fit
function: fm <- fit(..., data = data)
.
If fit
is set to NULL
the first argument ...
is ascores(fm)
.vcov(fm, order.by = order.by, data = data)
.vcov
the full sandwich
estimator or only the meat?z
or a formula with a single explanatory
variable like ~ z
. The observations in the model
are ordered by the size of z
. If set to NULL
(the
default) the observations are assumfit
function. Usually, this is not needed and ...
will be sufficient to pass arguments to fit
....
specification and the order.by
model. By default the variables are
taken from the environment which gefp
is called from.gefp
returns a list of class "gefp"
with components including:"zoo"
,Zeileis A. (2006), Implementing a Class of Structural Change Tests: An Econometric Computing Approach. Computational Statistics & Data Analysis, 50, 2987--3008. doi:10.1016/j.csda.2005.07.001.
Zeileis A., Hornik K. (2007), Generalized M-Fluctuation Tests for Parameter Instability, Statistica Neerlandica, 61, 488--508. doi:10.1111/j.1467-9574.2007.00371.x.
Zeileis A., Shah A., Patnaik I. (2010), Testing, Monitoring, and Dating Structural Changes in Exchange Rate Regimes, Computational Statistics and Data Analysis, Forthcoming. doi:10.1016/j.csda.2009.12.005.
efp
, efpFunctional
data("BostonHomicide")
gcus <- gefp(homicides ~ 1, family = poisson, vcov = kernHAC,
data = BostonHomicide)
plot(gcus, aggregate = FALSE)
gcus
sctest(gcus)
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