| gefp {strucchange} | R Documentation |
Computes an empirical M-fluctuation process from the scores of a fitted model.
gefp(..., fit = glm, scores = estfun, vcov = NULL, decorrelate = TRUE, sandwich = TRUE, order.by = NULL, fitArgs = NULL, parm = NULL, data = list())
... |
specification of some model which is passed together
with data to the fit function: fm <- fit(..., data = data).
If fit is set to NULL the first argument ...
is assumed to be already the fitted model fm
(all other arguments in ... are ignored and a warning
is issued in this case). |
fit |
a model fitting function, typically lm,
glm or rlm. |
scores |
a function which extracts the scores or estimating
function from the fitted object: scores(fm). |
vcov |
a function to extract the covariance matrix
for the coefficients of the fitted model:
vcov(fm, order.by = order.by, data = data). |
decorrelate |
logical. Should the process be decorrelated? |
sandwich |
logical. Is the function vcov the full sandwich
estimator or only the meat? |
order.by |
Either a vector 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 assumed to be ordered (e.g., a
time series). |
fitArgs |
List of additional arguments which could be passed to
the fit function. Usually, this is not needed and ...
will be sufficient to pass arguments to fit. |
parm |
integer or character specifying the component of the estimating functions which should be used (by default all components are used). |
data |
an optional data frame containing the variables in the ...
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 inlcuding
process |
the fitted empirical fluctuation process of class
"zoo", |
nreg |
the number of regressors, |
nobs |
the number of observations, |
fit |
the fit function used, |
scores |
the scores function used, |
fitted.model |
the fitted model. |
Zeileis A., Hornik K. (2003), Generalized M-Fluctuation Tests for Parameter Instability, Report 80, SFB "Adaptive Information Systems and Modelling in Economics and Management Science", Vienna University of Economics, http://www.wu-wien.ac.at/am/reports.htm#80.
Zeileis A. (2005), A Unified Approach to Structural Change Tests Based on ML Scores, F Statistics, and OLS Residuals. Econometric Reviews, 24, 445–466.
Zeileis A. (2006), Implementing a Class of Structural Change Tests: An Econometric Computing Approach. Computational Statistics & Data Analysis, 50, 2987–3008.
data("BostonHomicide")
gcus <- gefp(homicides ~ 1, family = poisson, vcov = kernHAC,
data = BostonHomicide)
plot(gcus, aggregate = FALSE)
gcus
sctest(gcus)